Machine Learning and the Physical Sciences, NeurIPS 2022

Machine Learning and the Physical Sciences
Workshop at the 36th conference on Neural Information Processing Systems (NeurIPS)
December 3, 2022
Submission Deadline: September 22 September 29, 2022, 23:59 AoE
Review Deadline: October 8 October 14, 2022, 23:59 AoE
Author (accept/reject) notification: October 15 October 20, 2022, 23:59 AoE
Camera-ready (final) paper deadline: November 19, 2022, 23:59 AoE
Poster deadline: November 19, 2022, 23:59 AoE
Workshop: December 3, 2022
The Machine Learning and the Physical Sciences workshop aims to provide an informal, inclusive and leading-edge venue for research and discussions at the interface of machine learning (ML) and the physical sciences. This interface spans (1) applications of ML in physical sciences (
ML for physics
), (2) developments in ML motivated by physical insights (
physics for ML
), and most recently (3) convergence of ML and physical sciences (
physics with ML
) which inspires questioning what scientific understanding means in the age of complex-AI powered science, and what roles machine and human scientists will play in developing scientific understanding in the future.
Recent years have seen a tremendous increase in cases where ML models are used for scientific processing and discovery, and similarly, instances where tools and insights from the physical sciences are brought to the study of ML models. The harmonious co-development of the two fields is not a surprise: ML methods have had great success in learning complex representations of data that enable novel modeling and data processing approaches in many scientific disciplines. Indeed, in some sense, ML and physics are concerned with a shared goal of characterizing the true probability distributions of nature. As ML and physical science research becomes more intertwined, questions naturally arise around what scientific understanding is when science is performed with the assistance of complex and highly parameterized models. Taken to the extreme, if an ML model is developed for a scientific task and demonstrates robustness and generalizability but lacks interpretability in terms of an existing scientific knowledge basis, is this still a useful scientific result?
The breadth of work at the intersection of ML and physical sciences is answering many important questions for both fields while opening up new ones that can only be addressed by a joint effort of both communities. By bringing together ML researchers and physical scientists who apply and study ML, we expect to strengthen the much needed interdisciplinary dialogue, introduce exciting new open problems to the broader community, and stimulate the production of new approaches to solving challenging open problems in the sciences. Invited talks from leading individuals in both communities will cover the state-of-the-art techniques and set the stage for this workshop, which will also include contributed talks selected from submissions. The workshop will also feature an expert panel discussion on "Philosophy of Science in the AI Era" --- focusing on topics such as scientific understanding in the age of extremely complex ML models, automating science via machines, and ML models as source of inspiration for scientific discoveries. Finally, there will be multiple community building activities such as a voluntary mentorship opportunity and round table discussions on curated topics to foster connection building and facilitate knowledge sharing across disciplines, backgrounds, and career stages.
NeurIPS 2022
The Machine Learning and the Physical Sciences 2022 workshop will be held on December 3, 2022 at the New Orleans Convention Center in New Orleans, USA as a part of the 36th annual conference on Neural Information Processing Systems (NeurIPS). The workshop is planned to take place in a hybrid format inclusive of virtual participation.
Papers
1
A Curriculum-Training-Based Strategy for Distributing Collocation Points during Physics-Informed Neural Network Training [ paper pdf ] [ poster ] [ event ]
Münzer, Marcus*; Bard, Christopher
2
A Neural Network Subgrid Model of the Early Stages of Planet Formation [ paper pdf ] [ poster ] [ event ]
Pfeil, Thomas*; Cranmer, Miles; Ho, Shirley; Armitage, Philip; Birnstiel, Tilman; Klahr, Hubert
3
A New Task: Deriving Semantic Class Targets for the Physical Sciences [ paper pdf ] [ poster ] [ event ]
Bowles, Micah R*
A Novel Automatic Mixed Precision Approach For Physics Informed Training [ paper pdf ] [ poster ] [ event ]
Xue, Jinze; Subramaniam, Akshay*; Hoemmen, Mark
5
A Self-Supervised Approach to Reconstruction in Sparse X-Ray Computed Tomography [ paper pdf ] [ poster ] [ event ]
Mendoza, Rey; Nguyen, Minh; Weng Zhu, Judith; Perciano, Talita; Dumont, Vincent; Mueller, Juliane; Ganapati, Vidya*
6
A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful [ paper pdf ] [ poster ] [ event ]
Hermans, Joeri; Delaunoy, Arnaud*; Rozet, François; Wehenkel, Antoine; Begy, Volodimir; Louppe, Gilles
7
A fast and flexible machine learning approach to data quality monitoring [ paper pdf ] [ poster ] [ event ]
Letizia, Marco*; Grosso, Gaia; Wulzer, Andrea; Zanetti, Marco; Pazzini, Jacopo; Rando, Marco; Lai, Nicolò
8
A hybrid Reduced Basis and Machine-Learning algorithm for building Surrogate Models: a first application to electromagnetism [ paper pdf ] [ event ]
Ribes, Alejandro*; Persicot, Ruben; Meyer, Lucas T; Ducreux, Jean-Pierre
9
A physics-informed search for metric solutions to Ricci flow, their embeddings, and visualisation [ paper pdf ] [ poster ] [ event ]
Jain, Aarjav*; Mishra, Challenger; Lió, Pietro
10
A probabilistic deep learning model to distinguish cusps and cores in dwarf galaxies [ paper pdf ] [ poster ] [ event ]
Expósito, Julen*; Huertas-Company, Marc; Di Cintio, Arianna; Brook, Chris; Macciò, Andrea; Grant, Rob; Arjona, Elena
11
A robust estimator of mutual information for deep learning interpretability [ paper pdf ] [ poster ] [ event ]
Piras, Davide*; Peris, Hiranya ; Pontzen, Andrew; Lucie-Smith, Luisa; Nord, Brian; Guo, Ningyuan (Lillian)
12
Ad-hoc Pulse Shape Simulation using Cyclic Positional U-Net [ paper pdf ] [ poster ] [ event ]
Li, Aobo*
Adaptive Selection of Atomic Fingerprints for High-Dimensional Neural Network Potentials [ paper pdf ] [ poster ] [ event ]
Sandberg, Johannes E*; Devijver, Emilie; Jakse, Noel; Voigtmann, Thomas
14
Addressing out-of-distribution data for flow-based gravitational wave inference [ paper pdf ] [ poster ] [ event ]
Maximillian, Dax*; Green, Stephen R; Wildberger, Jonas Bernhard; Gair, Jonathan; Puerrer, Michael; Macke, Jakob; Buonanno, Alessandra; Schölkopf, Bernhard
15
Adversarial Noise Injection for Learned Turbulence Simulations [ paper pdf ] [ poster ] [ event ]
Su, Jingtong*; Kempe, Julia; Fielding, Drummond; Tsilivis, Nikolaos; Cranmer, Miles; Ho, Shirley
16
Amortized Bayesian Inference for Supernovae in the Era of the Vera Rubin Observatory Using Normalizing Flows [ paper pdf ] [ poster ] [ event ]
Villar, Victoria A*
Amortized Bayesian Inference of GISAXS Data with Normalizing Flows [ paper pdf ] [ poster ] [ event ]
Zhdanov, Maksim*; Randolph, Lisa; Kluge, Thomas; Nakatsutsumi, Motoaki; Gutt, Christian; Ganeva, Marina; Hoffmann, Nico
18
Anomaly Detection with Multiple Reference Datasets in High Energy Physics [ paper pdf ] [ poster ] [ event ]
Chen, Mayee*; Nachman, Benjamin; Sala, Frederic
19
Applications of Differentiable Physics Simulations in Particle Accelerator Modeling [ paper pdf ] [ poster ] [ event ]
Roussel, Ryan*; Edelen, Auralee
20
Applying Deep Reinforcement Learning to the HP Model for Protein Structure Prediction [ paper pdf ] [ poster ] [ event ]
Yang, Kaiyuan*; Huang, Houjing; Vandans, Olafs; Murali, Adithyavairavan; Tian, Fujia; Yap, Roland H.C.; Dai, Liang
21
Astronomical Image Coaddition with Bundle-Adjusting Radiance Fields [ paper pdf ] [ poster ] [ event ]
Hutton, Harlan*; Palegar, Harshitha; Ho, Shirley; Cranmer, Miles; Melchior, Peter M; Eubank, Jenna
22
Atmospheric retrievals of exoplanets using learned parameterizations of pressure-temperature profiles [ paper pdf ] [ poster ] [ event ]
Gebhard, Timothy D*; Angerhausen, Daniel; Konrad, Björn; Alei, Eleonora; Quanz, Sascha; Schölkopf, Bernhard
23
CAPE: Channel-Attention-Based PDE Parameter Embeddings for SciML [ paper pdf ] [ poster ] [ event ]
Takamoto, Makoto*; Alesiani, Francesco; Niepert, Mathias
24
CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds [ paper pdf ] [ poster ] [ event ]
Cresswell, Jesse*; Ross, Brendan L; Loaiza-Ganem, Gabriel; Reyes-Gonzalez, Humberto; Letizia, Marco; Caterini, Anthony
25
Can denoising diffusion probabilistic models generate realistic astrophysical fields? [ paper pdf ] [ poster ] [ event ]
Mudur, Nayantara*; Finkbeiner, Douglas
Certified data-driven physics-informed greedy auto-encoder simulator [ paper pdf ] [ poster ] [ event ]
He, Xiaolong*; Choi, Youngsoo; Fries, William; Belof, Jonathan; Chen, Jiun-Shyan
27
Characterizing information loss in a chaotic double pendulum with the Information Bottleneck [ paper pdf ] [ poster ] [ event ]
Murphy, Kieran A*; Bassett, Danielle S
28
ClimFormer - a Spherical Transformer model for long-term climate projections [ paper pdf ] [ poster ] [ event ]
Ruhling Cachay, Salva; Mitra, Peetak P*; Kim, Sookyung; Hazarika, Subhashis; Hirasawa, Haruki; Hingmire, Dipti S; Singh, Hansi; Ramea, Kalai
29
Closing the resolution gap in Lyman alpha simulations with deep learning [ paper pdf ] [ poster ] [ event ]
Jacobus, Cooper H*; Harrington, Peter ; Lukić, Zarija
30
Clustering Behaviour of Physics-Informed Neural Networks: Inverse Modeling of An Idealized Ice Shelf [ paper pdf ] [ poster ] [ event ]
Iwasaki, Yunona*; Lai, Ching-Yao
Combinational-convolution for flow-based sampling algorithm [ paper pdf ] [ poster ] [ event ]
Tomiya, Akio*
32
Computing the Bayes-optimal classifier and exact maximum likelihood estimator with a semi-realistic generative model for jet physics [ paper pdf ] [ poster ] [ event ]
Cranmer, Kyle; Drnevich, Matthew*; Greenspan, Lauren; Macaluso, Sebastian; Pappadopulo, Duccio
33
Continual learning autoencoder training for a particle-in-cell simulation via streaming [ paper pdf ] [ poster ] [ event ]
Stiller, Patrick*; Makdani, Varun; Pöschel, Franz; Pausch, Richard; Debus, Alexander; Bussmann, Michael; Hoffmann, Nico
34
Contrasting random and learned features in deep Bayesian linear regression [ paper pdf ] [ poster ] [ event ]
Zavatone-Veth, Jacob A*; Tong, William; Pehlevan, Cengiz
35
Control and Calibration of GlueX Central Drift Chamber Using Gaussian Process Regression [ paper pdf ] [ poster ] [ event ]
McSpadden, Diana*; Jeske, Torri; Jarvis, Naomi; Lawrence, David; Britton, Thomas; Kalra, Nikhil
36
Cosmology from Galaxy Redshift Surveys with PointNet [ paper pdf ] [ poster ] [ event ]
Anagnostidis, Sotirios-Konstantinos*; Thomsen, Arne; Refregier, Alexandre; Kacprzak, Tomasz; Biggio, Luca; Hofmann, Thomas; Troester, Tilman
37
D-optimal neural exploration of nonlinear physical systems [ paper pdf ] [ poster ] [ event ]
Blanke, Matthieu*; Lelarge, Marc
DIGS: Deep Inference of Galaxy Spectra with Neural Posterior Estimation [ paper pdf ] [ poster ] [ event ]
Khullar, Gourav*; Nord, Brian; Ciprijanovic, Aleksandra; Poh, Jason; Xu, Fei; Samudre, Ashwin
39
DS-GPS : A Deep Statistical Graph Poisson Solver (for faster CFD simulations) [ paper pdf ] [ poster ] [ event ]
Nastorg, Matthieu*
Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian [ paper pdf ] [ poster ] [ event ]
So, Oswin*; Li, Gongjie; Theodorou, Evangelos; Tao, Molei
41
De-noising non-Gaussian fields in cosmology with normalizing flows [ paper pdf ] [ poster ] [ event ]
Rouhiainen, Adam*; Münchmeyer, Mortiz
Decay-aware neural network for event classification in collider physics [ paper pdf ] [ poster ] [ event ]
Kishimoto, Tomoe*; Morinaga, Masahiro; Saito, Masahiko; Tanaka, Junichi
43
Deconvolving Detector Effects for Distribution Moments [ paper pdf ] [ poster ] [ event ]
Desai, Krish*; Nachman, Benjamin; Thaler, Jesse
44
Decorrelation with Conditional Normalizing Flows [ paper pdf ] [ poster ] [ event ]
Klein, Samuel*; Golling, Tobias
Deep Learning Modeling of Subgrid Physics in Cosmological N-body Simulations [ paper pdf ] [ poster ] [ event ]
Chatziloizos, George-Mark; Lanusse, François; Cazenave, Tristan*
46
Deep Learning-Based Spatiotemporal Multi-Event Reconstruction for Delay-Line Detectors [ paper pdf ] [ poster ] [ event ]
Knipfer, Marco*; Gleyzer, Sergei; Meier, Stefan; Heimerl, Jonas; Hommelhoff, Peter
47
Deep-pretrained-FWI: combining supervised learning with physics-informed neural network [ paper pdf ] [ poster ] [ event ]
MULLER, ANA PAULA OLIVEIRA*; Bom , Clecio Roque; Costa, Jessé Carvalho; Faria, Elisângela Lopes ; de Albuquerque, Marcelo Portes ; de Albuquerque, Marcio Portes
48
Deformations of Boltzmann Distributions [ paper pdf ] [ poster ] [ event ]
Mate, Balint A*; Fleuret, François
49
Detecting structured signals in radio telescope data using RKHS [ paper pdf ] [ poster ] [ event ]
Tsuchida, Russell*; Yong, Suk Yee
50
Detection is truncation: studying source populations with truncated marginal neural ratio estimation [ paper pdf ] [ poster ] [ event ]
Anau Montel, Noemi*; Weniger, Christoph
51
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking [ paper pdf ] [ poster ] [ event ]
Corso, Gabriele*; Stärk, Hannes; Jing, Bowen; Barzilay, Dr.Regina; Jaakkola, Tommi
52
Differentiable Physics-based Greenhouse Simulation [ paper pdf ] [ poster ] [ event ]
Nguyen, Nhat M.*; Tran, Hieu; Duong, Minh; Bui, Hanh; Tran, Kenneth
53
Differentiable composition for model discovery [ paper pdf ] [ poster ] [ event ]
Rochman Sharabi, Omer*; Louppe, Gilles
54
Discovering Long-period Exoplanets using Deep Learning with Citizen Science Labels [ paper pdf ] [ poster ] [ event ]
Malik, Shreshth A*; Eisner, Nora; Lintott, Chris; Gal, Yarin
55
Diversity Balancing Generative Adversarial Networks for fast simulation of the Zero Degree Calorimeter in the ALICE experiment at CERN [ paper pdf ] [ poster ] [ event ]
Dubiński, Jan Michał *; Deja, Kamil; Wenzel, Sandro; Rokita, Przemysław; Trzcinski, Tomasz
56
Do Better QM9 Models Extrapolate as Better Quantum Chemical Property Predictors? [ paper pdf ] [ poster ] [ event ]
ZHANG, YUCHENG*; Charoenphakdee, Nontawat; Takamoto, So
57
Do graph neural networks learn jet substructure? [ paper pdf ] [ poster ] [ event ]
Mokhtar, Farouk*; Kansal, Raghav; Duarte, Javier
58
Domain Adaptation for Simulation-Based Dark Matter Searches with Strong Gravitational Lensing [ paper pdf ] [ poster ] [ event ]
Kumbam, Pranath Reddy; Gleyzer, Sergei; Toomey, Michael W*; Tidball, Marcos
59
Dynamical Mean Field Theory of Kernel Evolution in Wide Neural Networks [ paper pdf ] [ poster ] [ event ]
Bordelon, Blake A; Pehlevan, Cengiz*
60
Efficiently Moving Instead of Reweighting Collider Events with Machine Learning [ paper pdf ] [ poster ] [ event ]
Mastandrea, Radha*; Nachman, Benjamin
Elements of effective machine learning datasets in astronomy [ paper pdf ] [ poster ] [ event ]
Boscoe, Bernadette*; Do , Tuan
Employing CycleGANs to Generate Realistic STEM Images for Machine Learning [ paper pdf ] [ poster ] [ event ]
Khan, Abid A*; Lee, Chia-Hao; Pinshane, Huang; Clark, Bryan
63
Emulating Fast Processes in Climate Models [ paper pdf ] [ poster ] [ event ]
Brenowitz, Noah D*; Perkins, W. Andre; Nugent, Jacqueline M.; Watt-Meyer, Oliver; Clark, Spencer K.; Kwa, Anna; Henn, Brian; McGibbon, Jeremy; Bretherton, Christopher S.
64
Emulating cosmological growth functions with B-Splines [ paper pdf ] [ poster ] [ event ]
Kwan, Ngai Pok*; Modi, Chirag; Li, Yin; Ho, Shirley
65
Emulating cosmological multifields with generative adversarial networks [ paper pdf ] [ poster ] [ event ]
Andrianomena, Sambatra HS*; Hassan, Sultan; Villaescusa-Navarro, Francisco
66
Energy based models for tomography of quantum spin-lattice systems [ paper pdf ] [ poster ] [ event ]
J., Abhijith*; Vuffray, Marc D; Lokhov, Andrey
67
FO-PINNs: A First-Order formulation for Physics~Informed Neural Networks [ paper pdf ] [ poster ] [ event ]
Gladstone, Rini Jasmine*; Nabian, Mohammad Amin; Meidani, Hadi
68
Fast kinematics modeling for conjunction with lens image modeling [ paper pdf ] [ poster ] [ event ]
Gomer, Matthew R*; Biggio, Luca; Ertl, Sebastian; Wang, Han; Galan, Aymeric; Van de Vyvere, Lyne; Sluse, Dominique; Vernardos, Georgios; Suyu, Sherry
69
Finding NEEMo: Geometric Fitting using Neural Estimation of the Energy Mover’s Distance [ paper pdf ] [ poster ] [ event ]
Kitouni, Ouail*; Williams, Mike; Nolte, Niklas
70
Finding active galactic nuclei through Fink [ paper pdf ] [ poster ] [ event ]
Russeil, Etienne Sédick*; Ishida, Emille; Peloton, Julien; Moller, Anais; Le Montagner, Roman
71
First principles physics-informed neural network for quantum wavefunctions and eigenvalue surfaces [ paper pdf ] [ poster ] [ event ]
Mattheakis, Marios*; Schleder, Gabriel R; Larson, Daniel; Kaxiras, Efthimios
72
Flexible learning of quantum states with generative query neural networks [ event ]
Zhu, Yan; Wu, Ya-Dong*; Bai, Ge; Wang, Dong-Sheng; Wang, Yuexuan; Chiribella, Giulio
73
From Particles to Fluids: Dimensionality Reduction for Non-Maxwellian Plasma Velocity Distributions Validated in the Fluid Context [ paper pdf ] [ poster ] [ event ]
da Silva, Daniel E*
GAN-Flow: A dimension-reduced variational framework for physics-based inverse problems [ paper pdf ] [ poster ] [ event ]
Dasgupta, Agnimitra*; Patel, Dhruv; Ray, Deep; Johnson, Erik; Oberai, Assad
75
GAUCHE: A Library for Gaussian Processes in Chemistry [ paper pdf ] [ poster ] [ event ]
Griffiths, Ryan-Rhys*; Klarner, Leo; Moss, Henry B; Ravuri, Aditya; Truong, Sang; Rankovic, Bojana; Du, Yuanqi; Jamasb, Arian R.; Schwartz, Julius; Tripp, Austin J; Kell, Gregory; Bourached, Anthony; Chan, Alex J; Moss, Jacob; Guo, Chengzhi; Lee, Alpha; Schwaller, Philippe; Tang, Jian
76
Galaxy Morphological Classification with Deformable Attention Transformer [ paper pdf ] [ poster ] [ event ]
KANG, SEOKUN; Shin, Min-su; Kim, Taehwan*
77
Generating Calorimeter Showers as Point Clouds [ paper pdf ] [ poster ] [ event ]
Schnake, Simon Patrik*; Krücker, Dirk; Borras, Kerstin
78
Generating astronomical spectra from photometry with conditional diffusion models [ paper pdf ] [ poster ] [ event ]
Doorenbos, Lars*; Cavuoti, Stefano; Longo, Giuseppe; Brescia, Massimo; Sznitman, Raphael; Márquez Neila, Pablo
79
Geometric NeuralPDE (GNPnet) Models for Learning Dynamics [ paper pdf ] [ poster ] [ event ]
Fasina, Oluwadamilola Fasina*; Krishnaswamy, Smita; Krishnapriyan, Aditi
80
Geometric path augmentation for inference of sparsely observed stochastic nonlinear systems [ paper pdf ] [ poster ] [ event ]
Maoutsa, Dimitra*
Geometry-aware Autoregressive Models for Calorimeter Shower Simulations [ paper pdf ] [ poster ] [ event ]
Liu, Junze*; Ghosh, Aishik; Smith, Dylan; Baldi, Pierre; Whiteson, Daniel
82
Graph Structure from Point Clouds: Geometric Attention is All You Need [ paper pdf ] [ poster ] [ event ]
Murnane, Daniel*
83
Graphical Models are All You Need: Per-interaction reconstruction uncertainties in a dark matter detection experiment [ paper pdf ] [ poster ] [ event ]
Peters, Christina*; Higuera, Aaron; Liang, Shixiao; Bajwa, Waheed; Tunnell, Christopher
84
HGPflow: Particle reconstruction as hyperedge prediction [ paper pdf ] [ poster ] [ event ]
Dreyer, Etienne*; Kakati, Nilotpal; Armando Di Bello, Francesco
85
HIGlow: Conditional Normalizing Flows for High-Fidelity HI Map Modeling [ paper pdf ] [ poster ] [ event ]
Friedman, Roy*; Hassan, Sultan SH
86
How good is the Standard Model? Machine learning multivariate Goodness of Fit tests [ paper pdf ] [ poster ] [ event ]
Grosso, Gaia*; Letizia, Marco; Wulzer, Andrea; Pierini, Maurizio
87
HubbardNet: Efficient Predictions of the Bose-Hubbard Model Spectrum with Deep Neural Networks [ paper pdf ] [ poster ] [ event ]
Zhu , Ziyan*; Mattheakis, Marios; Pan, Weiwei; Kaxiras, Efthimios
88
Hybrid integration of the gravitational N-body problem with Artificial Neural Networks [ paper pdf ] [ poster ] [ event ]
Saz Ulibarrena, Veronica*; Portegies Zwart, Simon F; Sellentin, Elena; Koren, Barry; Horn, Philipp; Cai, Maxwell
89
HyperFNO: Improving the Generalization Behavior of Fourier Neural Operators [ paper pdf ] [ poster ] [ event ]
Alesiani, Francesco*; Takamoto, Makoto; Niepert, Mathias
90
Identifying AGN host galaxies with convolutional neural networks [ paper pdf ] [ poster ] [ event ]
Guo, Ziting*; Wu, John; Sharon, Chelsea
91
Identifying Hamiltonian Manifold in Neural Networks [ paper pdf ] [ poster ] [ event ]
Song, Yeongwoo; Jeong, Hawoong*
92
Improved Training of Physics-informed Neural Networks using Energy-Based priors: A Study on Electrical Impedance Tomography [ paper pdf ] [ poster ] [ event ]
Pokkunuru, Akarsh*; Rooshenas, Pedram; Strauss, Thilo; Abhishek, Anuj; Khan, Taufiquar R
93
Improving Generalization with Physical Equations [ paper pdf ] [ event ]
Wehenkel, Antoine*; Behrmann, Jens; Hsu, Hsiang; Sapiro, Guillermo; Louppe, Gilles; Jacobsen, Joern-Henrik
94
Inferring molecular complexity from mass spectrometry data using machine learning [ paper pdf ] [ poster ] [ event ]
Gebhard, Timothy D*; Bell, Aaron; Gong, Jian; Hastings, Jaden J. A.; Fricke, George M; Cabrol, Nathalie; Sandford, Scott; Phillips, Michael; Warren-Rhodes, Kimberley; Baydin, Atilim Gunes
95
Insight into cloud processes from unsupervised classification with a rotation-invariant autoencoder [ paper pdf ] [ poster ] [ event ]
Kurihana, Takuya*; Franke, James A; Foster, Ian; Wang, Ziwei; Moyer, Elisabeth
96
Interpretable Encoding of Galaxy Spectra [ paper pdf ] [ poster ] [ event ]
Liang, Yan*; Melchior, Peter M; Lu, Sicong
97
Intra-Event Aware Imitation Game for Fast Detector Simulation [ paper pdf ] [ poster ] [ event ]
Hashemi, Hosein*; Hartmann, Nikolai; Sharifzadeh, Sahand; Kahn, James; Kuhr, Thomas
98
Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows [ paper pdf ] [ poster ] [ event ]
Willmann, Anna*; Couperus Cabadağ, Jurjen Pieter; Chang, Yen-Yu; Pausch, Richard; Ghaith, Amin; Debus, Alexander; Irman, Arie; Bussmann, Michael; Schramm, Ulrich; Hoffmann, Nico
99
Learning Feynman Diagrams using Graph Neural Networks [ paper pdf ] [ poster ] [ event ]
Norcliffe, Alexander LI*; Mitchell, Harrison; Lió, Pietro
100
Learning Integrable Dynamics with Action-Angle Networks [ paper pdf ] [ poster ] [ event ]
Daigavane, Ameya*; Kosmala, Arthur; Cranmer, Miles; Smidt, Tess; Ho, Shirley
101
Learning Similarity Metrics for Volumetric Simulations with Multiscale CNNs [ paper pdf ] [ poster ] [ event ]
Kohl, Georg*; Chen, Liwei; Thuerey, Nils
102
Learning Uncertainties the Frequentist Way: Calibration and Correlation in High Energy Physics [ paper pdf ] [ poster ] [ event ]
Gambhir, Rikab*; Thaler, Jesse; Nachman, Benjamin
103
Learning dynamical systems: an example from open quantum system dynamics. [ paper pdf ] [ event ]
Novelli, Pietro*
Learning latent variable evolution for the functional renormalization group [ paper pdf ] [ poster ] [ event ]
Medvidović, Matija*; Toschi, Alessandro; Sangiovanni, Giorgio; Franchini, Cesare; Millis, Andy; Sengupta, Anirvan; Di Sante, Domenico
105
Learning the nonlinear manifold of extreme aerodynamics [ paper pdf ] [ poster ] [ event ]
Fukami, Kai*; Taira, Kunihiko
Learning-based solutions to nonlinear hyperbolic PDEs: Empirical insights on generalization errors [ paper pdf ] [ poster ] [ event ]
Thonnam Thodi, Bilal*; Ambadipudi, Sai Venkata Ramana; Jabari, Saif Eddin
107
Leveraging the Stochastic Predictions of Bayesian Neural Networks for Fluid Simulations [ paper pdf ] [ poster ] [ event ]
Mueller, Maximilian*; Greif, Robin; Jenko, Frank; Thuerey, Nils
108
Likelihood-Free Frequentist Inference for Calorimetric Muon Energy Measurement in High-Energy Physics [ paper pdf ] [ poster ] [ event ]
Masserano, Luca*; Lee, Ann; Izbicki, Rafael; Kuusela, Mikael; Dorigo, Tommaso
109
ML4LM: Machine Learning for Safely Landing on Mars [ paper pdf ] [ poster ] [ event ]
Wu, David D*; Chung, Wai Tong; Ihme, Matthias
111
Machine Learning for Chemical Reactions \\A Dance of Datasets and Models [ paper pdf ] [ poster ] [ event ]
Schreiner, Mathias*; Bhowmik, Arghya; Vegge, Tejs; Busk, Jonas; Jørgensen, Peter B; Winther, Ole
112
Machine learning for complete intersection Calabi-Yau manifolds [ paper pdf ] [ poster ] [ event ]
Erbin, Harold*; Tamaazousti, Mohamed; Finotello, Riccardo
113
Machine-learned climate model corrections from a global storm-resolving model [ paper pdf ] [ poster ] [ event ]
Kwa, Anna*
114
Modeling halo and central galaxy orientations on the SO(3) manifold with score-based generative models [ paper pdf ] [ poster ] [ event ]
Jagvaral, Yesukhei*; Lanusse, Francois; Mandelbaum, Rachel
115
Molecular Fingerprints for Robust and Efficient ML-Driven Molecular Generation [ paper pdf ] [ poster ] [ event ]
Tazhigulov, Ruslan N.*; Schiller, Joshua; Oppenheim, Jacob; Winston, Max
116
Monte Carlo Techniques for Addressing Large Errors and Missing Data in Simulation-based Inference [ paper pdf ] [ poster ] [ event ]
Wang, Bingjie*; Leja, Joel; Villar, Victoria A; Speagle, Joshua
117
Multi-Fidelity Transfer Learning for accurate database PDE approximation [ paper pdf ] [ poster ] [ event ]
Liu, Wenzhuo*; Yagoubi, Mouadh; Schoenauer, Marc; Danan, David
118
Multi-scale Digital Twin: Developing a fast and physics-infused surrogate model for groundwater contamination with uncertain climate models [ paper pdf ] [ poster ] [ event ]
Wang, Lijing*; Kurihana, Takuya; Meray, Aurelien; Mastilovic, Ilijana; Praveen, Satyarth; Xu, Zexuan; Memarzadeh, Milad; Lavin, Alexander; Wainwright, Haruko
119
NLP Inspired Training Mechanics For Modeling Transient Dynamics [ paper pdf ] [ poster ] [ event ]
Ghule, Lalit J*; Ranade, Rishikesh; Pathak, Jay
120
Neural Fields for Fast and Scalable Interpolation of Geophysical Ocean Variables [ paper pdf ] [ poster ] [ event ]
Johnson, Juan Emmanuel*; Lguensat, Redouane; fablet, ronan; Cosme, Emmanuel; Le Sommer, Julien
121
Neural Inference of Gaussian Processes for Time Series Data of Quasars [ paper pdf ] [ poster ] [ event ]
Danilov, Egor*; Ciprijanovic, Aleksandra; Nord, Brian
122
Neural Network Prior Mean for Particle Accelerator Injector Tuning [ paper pdf ] [ poster ] [ event ]
Xu, Connie *; Roussel, Ryan; Edelen, Auralee
123
Neural Network-based Real-Time Parameter Estimation in Electrochemical Sensors with Unknown Confounding Factors [ paper pdf ] [ poster ] [ event ]
Jariwala, Sarthak*, Yin, Yue; Jackson, Warren; Doris, Sean
124
Neuro-Symbolic Partial Differential Equation Solver [ paper pdf ] [ poster ] [ event ]
Akbari Mistani, Pouria*; Pakravan, Samira; Ilango, Rajesh; Choudhry, Sanjay; Gibou, Frederic
125
Normalizing Flows for Fragmentation and Hadronization [ paper pdf ] [ poster ] [ event ]
Youssef, Ahmed*; Ilten, Phil; Menzo, Tony; Zupan, Jure; Szewc, Manuel; Mrenna, Stephen; Wilkinson, Michael K.
126
Normalizing Flows for Hierarchical Bayesian Analysis: A Gravitational Wave Population Study [ paper pdf ] [ poster ] [ event ]
Ruhe, David*; Wong, Kaze; Cranmer, Miles; Forré, Patrick
127
Offline Model-Based Reinforcement Learning for Tokamak Control [ paper pdf ] [ poster ] [ event ]
Char, Ian*; Abbate, Joseph; Bardoczi, Laszlo; Boyer, Mark; Chung, Youngseog; Conlin, Rory; Erickson, Keith; Mehta, Viraj; Richner, Nathan; Kolemen, Egemen; Schneider, Jeff
128
On Using Deep Learning Proxies as Forward Models in Optimization Problems [ paper pdf ] [ poster ] [ event ]
Albreiki, Fatima A*; Belayouni, Nidhal; Gupta, Deepak K
129
One Network to Approximate Them All: Amortized Variational Inference of Ising Ground States [ paper pdf ] [ poster ] [ event ]
Sanokowski, Sebastian*; Berghammer, Wilhelm; Kofler, Johannes; Hochreiter, Sepp; Lehner, Sebastian
130
One-Class Dense Networks for Anomaly Detection [ paper pdf ] [ poster ] [ event ]
Karr, Norman*; Nachman, Benjamin; Shih, David
131
One-shot learning for solution operators of partial differential equations [ paper pdf ] [ poster ] [ event ]
Lu, Lu*; Jiao, Anran; Pathak, Jay; Ranade, Rishikesh; He, Haiyang
132
PELICAN: Permutation Equivariant and Lorentz Invariant or Covariant Aggregator Network for Particle Physics [ paper pdf ] [ poster ] [ event ]
Offermann, Jan*; Bogatskiy, Alexander; Hoffman, Timothy; Miller, David
133
PIPS: Path Integral Stochastic Optimal Control for Path Sampling in Molecular Dynamics [ event ]
Holdijk, Lars*; Du, Yuanqi; Hooft, Ferry; Jaini, Priyank; Ensing, Bernd; Welling, Max
134
Particle-level Compression for New Physics Searches [ paper pdf ] [ poster ] [ event ]
Huang, Yifeng*; Collins, Jack; Nachman, Benjamin; Knapen, Simon; Whiteson, Daniel
135
Phase transitions and structure formation in learning local rules [ paper pdf ] [ poster ] [ event ]
Zunkovic, Bojan*; Ilievski, Enej
Physical Data Models in Machine Learning Imaging Pipelines [ paper pdf ] [ event ]
Aversa, Marco*; Oala, Luis; Clausen, Christoph; Murray-Smith, Roderick; Sanguinetti, Bruno
137
Physics solutions for privacy leaks in machine learning [ paper pdf ] [ poster ] [ event ]
Pozas-Kerstjens, Alejandro*; Hernandez-Santana, Senaida; Pareja Monturiol, Jose Ramon; Castrillon Lopez, Marco; Scarpa, Giannicola; Gonzalez-Guillen, Carlos E.; Perez-Garcia, David
138
Physics-Driven Convolutional Autoencoder Approach for CFD Data Compressions [ paper pdf ] [ poster ] [ event ]
Olmo, Alberto*; Zamzam, Ahmed S; Glaws, Andrew; King, Ryan
139
Physics-Informed CNNs for Super-Resolution of Sparse Observations on Dynamical Systems [ paper pdf ] [ poster ] [ event ]
Kelshaw, Daniel J*; Rigas, Georgios; Magri, Luca
140
Physics-Informed Convolutional Neural Networks for Corruption Removal on Dynamical Systems [ paper pdf ] [ poster ] [ event ]
Kelshaw, Daniel J*; Magri, Luca
141
Physics-Informed Machine Learning of Dynamical Systems for Efficient Bayesian Inference [ paper pdf ] [ poster ] [ event ]
Dhulipala, Som*; Che, Yifeng; Shields, Michael
142
Physics-Informed Neural Networks as Solvers for the Time-Dependent Schrödinger Equation [ paper pdf ] [ poster ] [ event ]
Shah, Karan*; Stiller, Patrick; Hoffmann, Nico; Cangi, Attila
143
Physics-informed Bayesian Optimization of an Electron Microscope [ event ]
Ma, Desheng*
Physics-informed neural networks for modeling rate- and temperature-dependent plasticity [ paper pdf ] [ event ]
Arora, Rajat; Kakkar, Pratik; Amit, Chakraborty; Dey, Biswadip*
145
Plausible Adversarial Attacks on Direct Parameter Inference Models in Astrophysics [ paper pdf ] [ poster ] [ event ]
Horowitz, Benjamin A*; Melchior, Peter M
146
Point Cloud Generation using Transformer Encoders and Normalising Flows [ paper pdf ] [ poster ] [ event ]
Käch, Benno*; Krücker, Dirk; Melzer, Isabell
147
Posterior samples of source galaxies in strong gravitational lenses with score-based priors [ paper pdf ] [ event ]
Adam, Alexandre*; Coogan, Adam; Malkin, Nikolay; Legin, Ronan; Perreault-Levasseur, Laurence; Hezaveh, Yashar; Bengio, Yoshua
148
Probabilistic Mixture Modeling For End-Member Extraction in Hyperspectral Data [ paper pdf ] [ event ]
Hoidn, Oliver*; Mishra, Aashwin; Mehta, Apurva
149
Qubit seriation: Undoing data shuffling using spectral ordering [ paper pdf ] [ poster ] [ event ]
Acharya, Atithi*; Rudolph, Manuel; Chen, Jing; Miller, Jacob; Perdemo-Ortiz, Alejandro
150
Real-time Health Monitoring of Heat Exchangers using Hypernetworks and PINNs [ paper pdf ] [ poster ] [ event ]
Majumdar, Ritam; Jadhav, Vishal; Deodhar, Anirudh; Karande, Shirish; Vig, Lovekesh; Runkana, Venkataramana*
151
Recovering Galaxy Cluster Convergence from Lensed CMB with Generative Adversarial Networks [ paper pdf ] [ poster ] [ event ]
Parker, Liam H*; Han, Dongwon; Ho, Shirley; Lemos, Pablo
152
Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators [ paper pdf ] [ poster ] [ event ]
Bilbrey, Jenna A*; Herman, Kristina; Sprueill, Henry; Xantheas, Sotiris; Das, Payel; Lopez Roldan, Manuel; Kraus, Mike; Helal, Hatem; Choudhury, Sutanay
153
Renormalization in the neural network-quantum field theory correspondence [ paper pdf ] [ poster ] [ event ]
Erbin, Harold*; Lahoche, Vincent; Ousmane Samary, Dine
154
SE(3)-equivariant self-attention via invariant features [ paper pdf ] [ poster ] [ event ]
Chen, Nan*; Villar, Soledad
Scalable Bayesian Inference for Finding Strong Gravitational Lenses [ paper pdf ] [ poster ] [ event ]
Patel, Yash P*; Regier, Jeffrey
156
Score Matching via Differentiable Physics [ paper pdf ] [ poster ] [ event ]
Holzschuh, Benjamin J*; Vegetti, Simona ; Thuerey, Nils
157
Score-based Seismic Inverse Problems [ paper pdf ] [ poster ] [ event ]
Ravula, Sriram*; Voytan, Dimitri P; Liebman, Elad; Tuvi, Ram; Gandhi, Yash; Ghani, Hamza H ; Ardel, Alexandre; Sen, Mrinal; Dimakis, Alex
158
Self-supervised detection of atmospheric phenomena from remotely sensed synthetic aperture radar imagery [ paper pdf ] [ poster ] [ event ]
Glaser, Yannik*; Sadowski, Peter; Stopa, Justin
159
Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection [ paper pdf ] [ poster ] [ event ]
Ciprijanovic, Aleksandra*; Lewis, Ashia; Pedro, Kevin; Madireddy, Sandeep; Nord, Brian; Perdue, Gabriel Nathan; Wild, Stefan
160
Set-Conditional Set Generation for Particle Physics [ paper pdf ] [ poster ] [ event ]
Ganguly, Sanmay; Heinrich, Lukas*; Kakati, Nilotpal; Soybelman, Nathalie
161
Shining light on data [ paper pdf ] [ poster ] [ event ]
Kumar, Akshat*; Sarovar, Mohan
Simplifying Polylogarithms with Machine Learning [ paper pdf ] [ poster ] [ event ]
Dersy, Aurelien*; Schwartz, Matthew; Zhang, Xiaoyuan
163
Simulation-based inference of the 2D ex-situ stellar mass fraction distribution of galaxies using variational autoencoders [ paper pdf ] [ poster ] [ event ]
Angeloudi, Eirini*; Huertas-Company, Marc; Falcón-Barroso, Jesús; Sarmiento, Regina; Walo-Martín, Daniel; Pillepich, Annalisa; Vega Ferrero, Jesús
164
Skip Connections for High Precision Regressors [ paper pdf ] [ poster ] [ event ]
Paul, Ayan*; Bishara, Fady; Dy, Jennifer
165
Source Identification and Field Reconstruction of Advection-Diffusion Process from Sparse Sensor Measurements [ paper pdf ] [ poster ] [ event ]
Daw, Arka*; Yeo, Kyongmin; Karpatne, Anuj; Klein, Levente
166
Stabilization and Acceleration of CFD Simulation by Controlling Relaxation Factor Based on Residues: An SNN Based Approach [ paper pdf ] [ poster ] [ event ]
Dey, Sounak*; Banerjee, Dighanchal; Maurya, Mithilesh; Ahmad, Dilshad
167
Statistical Inference for Coadded Astronomical Images [ paper pdf ] [ poster ] [ event ]
Wang, Mallory; Mendoza, Ismael*; Regier, Jeffrey; Avestruz, Camille; Wang, Cheng
168
Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference [ paper pdf ] [ poster ] [ event ]
Poh, Jason*; Samudre, Ashwin; Ciprijanovic, Aleksandra; Nord, Brian; Frieman, Joshua; Khullar, Gourav
169
Strong-Lensing Source Reconstruction with Denoising Diffusion Restoration Models [ paper pdf ] [ poster ] [ event ]
Karchev, Kosio*; Anau Montel, Noemi; Coogan, Adam; Weniger, Christoph
170
SuNeRF: Validation of a 3D Global Reconstruction of the Solar Corona Using Simulated EUV Images [ paper pdf ] [ poster ] [ event ]
Bintsi, Kyriaki-Margarita*; Jarolim, Robert; Tremblay, Benoit; Santos, Miraflor P; Jungbluth, Anna; Mason, James; Sundaresan, Sairam; Vourlidas, Angelos; Downs, Cooper; Caplan, Ronald; Muñoz-Jaramillo, Andrés
171
Super-resolving Dark Matter Halos using Generative Deep Learning [ paper pdf ] [ poster ] [ event ]
Schaurecker, David*
Tensor networks for active inference with discrete observation spaces [ paper pdf ] [ poster ] [ event ]
Wauthier, Samuel T*; Vanhecke, Bram; Verbelen, Tim; Dhoedt, Bart
173
The Senseiver: attention-based global field reconstruction from sparse observations [ paper pdf ] [ poster ] [ event ]
Santos, Javier E*; Fox, Zachary; Mohan, Arvind T; Viswanathan, Hari S; Lubbers, NIcholas
174
Thermophysical Change Detection on the Moon with the Lunar Reconnaissance Orbiter Diviner sensor [ paper pdf ] [ poster ] [ event ]
Delgado-Centeno, Jose Ignacio*; Bucci, Silvia; Liang, Ziyi; Gaffinet, Ben; Bickel, Valentin T; Moseley, Ben; Olivares, Miguel
175
Time-aware Bayesian optimization for adaptive particle accelerator tuning [ paper pdf ] [ poster ] [ event ]
Kuklev, Nikita*; Sun, Yine; Shang, Hairong; Borland, Michael; Fystro, Gregory
176
Thomas, Dawson S*; Demers, Sarah; Krishnaswamy, Smita; Rieck, Bastian A
177
Towards Creating Benchmark Datasets of Universal Neural Network Potential for Material Discovery [ paper pdf ] [ poster ] [ event ]
Takamoto, So*; Shinagawa, Chikashi; Charoenphakdee, Nontawat
178
Towards a non-Gaussian Generative Model of large-scale Reionization Maps [ paper pdf ] [ poster ] [ event ]
Lin, Yu-Heng*; Hassan, Sultan SH; Régaldo-Saint Blancard, Bruno; Eickenberg, Michael; Modi, Chirag
179
Towards solving model bias in cosmic shear forward modeling [ paper pdf ] [ poster ] [ event ]
Remy, Benjamin*; Lanusse, Francois; Starck, Jean-Luc
180
Training physical networks like neural networks: deep physical neural networks [ paper pdf ] [ poster ] [ event ]
Wright, Logan*; Onodera, Tatsuhiro; Stein, Martin; Wang, Tianyu; Schachter, Darren; Hu, Zoey; McMahon, Peter
181
Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows [ paper pdf ] [ poster ] [ event ]
Pellegrin, Raphael PF*; Bullwinkel, Jeffrey B; Mattheakis, Marios; Protopapas, Pavlos
182
Uncertainty Aware Deep Learning for Particle Accelerators [ paper pdf ] [ poster ] [ event ]
Rajput, Kishansingh*; Schram, Malachi; Somayaji, Karthik
183
Uncertainty quantification methods for ML-based surrogate models of scientific applications [ paper pdf ] [ poster ] [ event ]
Basu, Kishore; Hao, Judy; Hintz, Delphine ; Shah, Dev; Palmer, Aaron; Hora, Gurpreet Singh; Nwankwo, Darian; White, Laurent*
184
Using Shadows to Learn Ground State Properties of Quantum Hamiltonians [ paper pdf ] [ poster ] [ event ]
Tran, Viet T.*; Lewis, Laura; Kofler, Johannes; Huang, Hsin-Yuan; Kueng, Richard; Hochreiter, Sepp; Lehner, Sebastian
185
Validation Diagnostics for SBI algorithms based on Normalizing Flows [ paper pdf ] [ poster ] [ event ]
Linhart, Julia*; Gramfort, Alexandre ; Rodrigues, Pedro
186
Virgo: Scalable Unsupervised Classification of Cosmological Shock Waves [ paper pdf ] [ poster ] [ event ]
Lamparth, Max*; Böss, Ludwig; Steinwandel, Ulrich; Dolag, Klaus
187
Wavelets Beat Monkeys at Adversarial Robustness [ paper pdf ] [ poster ] [ event ]
Su, Jingtong*; Kempe, Julia