Pablo Lemos

Publication Activity (10 Years)

Years Active: 2022-2024
Publications (10 Years): 20

Top Topics

Probability Mass

Metropolis Hastings

Bayesian Inference

Top Venues

Mach. Learn. Sci. Technol.

Publications

Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin
On diffusion models for amortized inference: Benchmarking and improving stochastic control and sampling. CoRR (2024)
Tara Akhound-Sadegh, Jarrid Rector-Brooks, Avishek Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. CoRR (2024)
Pablo Lemos, Sammy Sharief, Nikolay Malkin, Laurence Perreault Levasseur, Yashar Hezaveh
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation. CoRR (2024)
Matthew Ho, Deaglan J. Bartlett, Nicolas Chartier, Carolina Cuesta-Lázaro, Simon Ding, Axel Lapel, Pablo Lemos, Christopher C. Lovell, T. Lucas Makinen, Chirag Modi, Viraj Pandya, Shivam Pandey, Lucia A. Perez, Benjamin D. Wandelt, Greg L. Bryan
LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology. CoRR (2024)
Siddarth Venkatraman, Moksh Jain, Luca Scimeca, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yoshua Bengio, Glen Berseth, Nikolay Malkin
Amortizing intractable inference in diffusion models for vision, language, and control. CoRR (2024)
Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael M. Bronstein, Alexander Tong, Avishek Joey Bose
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation. CoRR (2024)
Noe Dia, M. J. Yantovski-Barth, Alexandre Adam, Micah Bowles, Pablo Lemos, Anna M. M. Scaife, Yashar Hezaveh, Laurence Perreault Levasseur
Bayesian Imaging for Radio Interferometry with Score-Based Priors. CoRR (2023)
Pablo Lemos, Adam Coogan, Yashar Hezaveh, Laurence Perreault Levasseur
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference. CoRR (2023)
Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin
A theory of continuous generative flow networks. CoRR (2023)
Pablo Lemos, Niall Jeffrey, Miles D. Cranmer, Shirley Ho, Peter W. Battaglia
Rediscovering orbital mechanics with machine learning. Mach. Learn. Sci. Technol. 4 (4) (2023)
Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault Levasseur
Improving Gradient-guided Nested Sampling for Posterior Inference. CoRR (2023)
Salem Lahlou, Tristan Deleu, Pablo Lemos, Dinghuai Zhang, Alexandra Volokhova, Alex Hernández-García, Léna Néhale Ezzine, Yoshua Bengio, Nikolay Malkin
A theory of continuous generative flow networks. ICML (2023)
Pablo Lemos, Adam Coogan, Yashar Hezaveh, Laurence Perreault Levasseur
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference. ICML (2023)
Pablo Lemos, Miles D. Cranmer, Muntazir Abidi, ChangHoon Hahn, Michael Eickenberg, Elena Massara, David Yallup, Shirley Ho
Robust simulation-based inference in cosmology with Bayesian neural networks. Mach. Learn. Sci. Technol. 4 (1) (2023)
Alexandra Volokhova, Michal Koziarski, Alex Hernández-García, Cheng-Hao Liu, Santiago Miret, Pablo Lemos, Luca A. Thiede, Zichao Yan, Alán Aspuru-Guzik, Yoshua Bengio
Towards equilibrium molecular conformation generation with GFlowNets. CoRR (2023)
Pablo Lemos, Liam Holden Parker, ChangHoon Hahn, Shirley Ho, Michael Eickenberg, Jiamin Hou, Elena Massara, Chirag Modi, Azadeh Moradinezhad Dizgah, Bruno Régaldo-Saint Blancard, David N. Spergel
SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering. CoRR (2023)
Harry T. J. Bevins, William J. Handley, Pablo Lemos, Peter H. Sims, Eloy de Lera Acedo, Anastasia Fialkov, Justin Alsing
Removing the fat from your posterior samples with margarine. CoRR (2022)
Pablo Lemos, Niall Jeffrey, Miles D. Cranmer, Shirley Ho, Peter W. Battaglia
Rediscovering orbital mechanics with machine learning. CoRR (2022)
Pablo Lemos, Miles D. Cranmer, Muntazir Abidi, ChangHoon Hahn, Michael Eickenberg, Elena Massara, David Yallup, Shirley Ho
Robust Simulation-Based Inference in Cosmology with Bayesian Neural Networks. CoRR (2022)
David Yallup, Will Handley, Mike Hobson, Anthony N. Lasenby, Pablo Lemos
Split personalities in Bayesian Neural Networks: the case for full marginalisation. CoRR (2022)