98 citations · 365 across the 15 of their papers we have counts for
4 papers · 1 filter
Improved Contrastive Divergence Training of Energy Based Models
Yilun Du, Shuang Li, Joshua Tenenbaum +1
Contrastive divergence is a popular method of training energy-based models, but is known to have difficulties with training stability. We propose an adaptation to improve contrasti…
Energy-Based Models for Continual Learning
Shuang Li, Yilun Du, Gido M. van de Ven +1
We motivate Energy-Based Models (EBMs) as a promising model class for continual learning problems. Instead of tackling continual learning via the use of external memory, growing mo…
Compositional Visual Generation and Inference with Energy Based Models
Yilun Du, Shuang Li, Igor Mordatch
A vital aspect of human intelligence is the ability to compose increasingly complex concepts out of simpler ideas, enabling both rapid learning and adaptation of knowledge. In this…
Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks
Joseph Suarez, Yilun Du, Igor Mordatch +1
Progress in multiagent intelligence research is fundamentally limited by the number and quality of environments available for study. In recent years, simulated games have become a…