activity
20142025
most citedGenerative Adversarial Networks

4.6k citations · 7.2k across the 13 of their papers we have counts for

collaborators

13 papers

cs.CY2025

In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate?

Ben Bucknall, Saad Siddiqui, Lara Thurnherr +19

International cooperation is common in AI research, including between geopolitical rivals. While many experts advocate for greater international cooperation on AI safety to address…

cs.LG2023

Learning to Scale Logits for Temperature-Conditional GFlowNets

Minsu Kim, Joohwan Ko, Taeyoung Yun +6

GFlowNets are probabilistic models that sequentially generate compositional structures through a stochastic policy. Among GFlowNets, temperature-conditional GFlowNets can introduce…

cs.LG2023

Delta-AI: Local objectives for amortized inference in sparse graphical models

Jean-Pierre Falet, Hae Beom Lee, Esmeralda S. Whitammer +6

We present a new algorithm for amortized inference in sparse probabilistic graphical models (PGMs), which we call -amortized inference (-AI). Our approach is based on the obs…

cs.LG2022★ 5 cited

Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning

Aniket Didolkar, Kshitij Gupta, Anirudh Goyal +4

Recurrent neural networks have a strong inductive bias towards learning temporally compressed representations, as the entire history of a sequence is represented by a single vector…

cs.LG2019★ 62 cited

Maximum Entropy Generators for Energy-Based Models

Rithesh Kumar, Sherjil Ozair, Anirudh Goyal +2

Maximum likelihood estimation of energy-based models is a challenging problem due to the intractability of the log-likelihood gradient. In this work, we propose learning both the e…

stat.ML2018★ 1.7k cited

Learning deep representations by mutual information estimation and maximization

R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon +4

In this work, we perform unsupervised learning of representations by maximizing mutual information between an input and the output of a deep neural network encoder. Importantly, we…