Uros Seljak

30 papers A* 3Journal 25Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?
CoRR
Emanuel Sommer, Kangning Diao, Jakob Robnik, Uros Seljak, David Rügamer
2026 J jnl
Counterdiabatic Hamiltonian Monte Carlo.
CoRR
Reuben Cohn-Gordon, Uros Seljak, Dries Sels
2025 J jnl
Initial Conditions from Galaxies: Machine-Learning Subgrid Correction to Standard Reconstruction.
CoRR
Liam Parker, Adrian E. Bayer, Uros Seljak
2025 A* conf
Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks.
ICLR
Emanuel Sommer, Jakob Robnik, Giorgi Nozadze, Uros Seljak, David Rügamer
2025 J jnl
Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks.
CoRR
Emanuel Sommer, Jakob Robnik, Giorgi Nozadze, Uros Seljak, David Rügamer
2025 J jnl
Persistent Sampling: Enhancing the Efficiency of Sequential Monte Carlo.
Stat. Comput.
Minas Karamanis, Uros Seljak
2025 J jnl
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS).
CoRR
Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille L. Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia S. Dong, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutierrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang
2024 — conf
Fluctuation without dissipation: Microcanonical Langevin Monte Carlo.
AABI
Jakob Robnik, Uros Seljak
2024 J jnl
Persistent Sampling: Unleashing the Potential of Sequential Monte Carlo.
CoRR
Minas Karamanis, Uros Seljak
2023 J jnl
Deterministic Langevin Unconstrained Optimization with Normalizing Flows.
CoRR
James M. Sullivan, Uros Seljak
2023 J jnl
Microcanonical Hamiltonian Monte Carlo.
J. Mach. Learn. Res.
Jakob Robnik, Giuseppe Bruno De Luca, Eva Silverstein, Uros Seljak
2023 J jnl
Multiscale Flow for Robust and Optimal Cosmological Analysis.
CoRR
Biwei Dai, Uros Seljak
2022 J jnl
A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time Series.
CoRR
George Stein, Uros Seljak, Vanessa Böhm, G. Aldering, P. Antilogus, C. Aragon, S. Bailey, C. Baltay, Sébastien Bongard, K. Boone, C. Buton, Y. Copin, S. Dixon, Dominique Fouchez, Emmanuel Gangler, R. Gupta, Brian Hayden, W. Hillebrandt, M. Karmen, A. G. Kim, M. Kowalski, D. Kusters, Pierre-François Léget, F. Mondon, J. Nordin, R. Pain, E. Pecontal, R. Pereira, S. Perlmutter, K. A. Ponder, D. Rabinowitz, M. Rigault, D. Rubin, K. Runge, C. Saunders, G. Smadja, N. Suzuki, C. Tao, Rollin C. Thomas, Maria Vincenzi
2022 A* conf
Deterministic Langevin Monte Carlo with Normalizing Flows for Bayesian Inference.
NeurIPS
Richard D. P. Grumitt, Biwei Dai, Uros Seljak
2022 J jnl
Deterministic Langevin Monte Carlo with Normalizing Flows for Bayesian Inference.
CoRR
Uros Seljak, Richard D. P. Grumitt, Biwei Dai
2022 J jnl
Probabilistic Autoencoder.
Trans. Mach. Learn. Res.
Vanessa M. Boehm, Uros Seljak
2022 J jnl
Statistical Significance Testing for Mixed Priors: A Combined Bayesian and Frequentist Analysis.
Entropy
Jakob Robnik, Uros Seljak
2022 J jnl
Translation and Rotation Equivariant Normalizing Flow (TRENF) for Optimal Cosmological Analysis.
CoRR
Biwei Dai, Uros Seljak
2022 J jnl
pocoMC: A Python package for accelerated Bayesian inference in astronomy and cosmology.
J. Open Source Softw.
Minas Karamanis, David Nabergoj, Florian Beutler, John A. Peacock, Uros Seljak
2021 J jnl
FlowPM: Distributed TensorFlow implementation of the FastPM cosmological N-body solver.
Astron. Comput.
Chirag Modi, François Lanusse, Uros Seljak
2021 A* conf
Sliced Iterative Normalizing Flows.
ICML
Biwei Dai, Uros Seljak
2020 J jnl
Learning effective physical laws for generating cosmological hydrodynamics with Lagrangian Deep Learning.
CoRR
Biwei Dai, Uros Seljak
2020 J jnl
Probabilistic Auto-Encoder.
CoRR
Vanessa Böhm, Uros Seljak
2020 J jnl
Sliced Iterative Generator.
CoRR
Biwei Dai, Uros Seljak
2020 J jnl
Unsupervised in-distribution anomaly detection of new physics through conditional density estimation.
CoRR
George Stein, Uros Seljak, Biwei Dai
2019 J jnl
Generative Learning of Counterfactual for Synthetic Control Applications in Econometrics.
CoRR
Chirag Modi, Uros Seljak
2019 — conf
Normalizing Constant Estimation with Gaussianized Bridge Sampling.
AABI
He Jia, Uros Seljak
2019 J jnl
Normalizing Constant Estimation with Gaussianized Bridge Sampling.
CoRR
He Jia, Uros Seljak
2019 J jnl
Posterior inference unchained with EL_2O.
CoRR
Uros Seljak, Byeonghee Yu
2019 J jnl
Uncertainty Quantification with Generative Models.
CoRR
Vanessa Böhm, François Lanusse, Uros Seljak