Tomas Geffner

According to our database, Tomas Geffner authored at least 20 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Deep End-to-end Causal Inference.

Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Agrin Hilmkil, Joel Jennings, Meyer Scetbon, Miltiadis Allamanis, Cheng Zhang

Trans. Mach. Learn. Res., 2024

Energy-Based Diffusion Language Models for Text Generation.

Minkai Xu, Tomas Geffner, Karsten Kreis, Weili Nie, Yilun Xu, Jure Leskovec, Stefano Ermon, Arash Vahdat

CoRR, 2024

Stochastic Flow Matching for Resolving Small-Scale Physics.

Stathi Fotiadis, Noah D. Brenowitz, Tomas Geffner, Yair Cohen, Michael S. Pritchard, Arash Vahdat, Morteza Mardani

CoRR, 2024

Truncated Consistency Models.

Sangyun Lee, Yilun Xu, Tomas Geffner, Giulia Fanti, Karsten Kreis, Arash Vahdat, Weili Nie

CoRR, 2024

Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization.

Siyi Gu, Minkai Xu, Alexander S. Powers, Weili Nie, Tomas Geffner, Karsten Kreis, Jure Leskovec, Arash Vahdat, Stefano Ermon

CoRR, 2024

Joint control variate for faster black-box variational inference.

Xi Wang, Tomas Geffner, Justin Domke

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Compositional Score Modeling for Simulation-Based Inference.

Tomas Geffner, George Papamakarios, Andriy Mnih

Proceedings of the International Conference on Machine Learning, 2023

Langevin Diffusion Variational Inference.

Tomas Geffner, Justin Domke

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

A Dual Control Variate for doubly stochastic optimization and black-box variational inference.

Xi Wang, Tomas Geffner, Justin Domke

CoRR, 2022

Score Modeling for Simulation-based Inference.

Tomas Geffner, George Papamakarios, Andriy Mnih

CoRR, 2022

Deep End-to-end Causal Inference.

Tomas Geffner, Javier Antorán, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang

CoRR, 2022

Variational Inference with Locally Enhanced Bounds for Hierarchical Models.

Tomas Geffner, Justin Domke

Proceedings of the International Conference on Machine Learning, 2022

2021

Empirical Evaluation of Biased Methods for Alpha Divergence Minimization.

Tomas Geffner, Justin Domke

CoRR, 2021

MCMC Variational Inference via Uncorrected Hamiltonian Annealing.

Tomas Geffner, Justin Domke

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the difficulty of unbiased alpha divergence minimization.

Tomas Geffner, Justin Domke

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Approximation Based Variance Reduction for Reparameterization Gradients.

Tomas Geffner, Justin Domke

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Rule for Gradient Estimator Selection, with an Application to Variational Inference.

Tomas Geffner, Justin Domke

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2018

Using Large Ensembles of Control Variates for Variational Inference.

Tomas Geffner, Justin Domke

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Compact Policies for Fully Observable Non-Deterministic Planning as SAT.

Tomas Geffner, Hector Geffner

Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling, 2018

2015

Width-Based Planning for General Video-Game Playing.

Tomas Geffner, Hector Geffner

Proceedings of the Eleventh AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2015