46 citations · 177 across the 41 of their papers we have counts for
8 papers · 1 filter
Visualizing the World Model in an Agent's Value Function
Shawheen Naderi, Fatemeh Akherati, Yubei Chen
Could model-free reinforcement learning algorithms actually be learning a model of the environment? In this work, we apply counterfactual interventions which hold everything about…
Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction
Xinyi Li, Zaishuo Xia, Chenjie Hao +1
World models are expected to support imagination over extended temporal horizons, yet most are still trained through local few-step prediction objectives and deployed by recursivel…
Toward a mechanistic understanding of inference in visual cortex and diffusion models
Zeyu Yun, Alexander Belsten, Dasheng Bi +3
We describe a model of perceptual inference in primary visual cortex (V1) equivalent to a minimal diffusion model whose function can be readily understood from its parameters. The…
Improving Weak World Models Behind Strong Agents in Atari Pong
Yukuan Lu, Zaishuo Xia, Weyl Lu +1
Strong world-model agents frequently contain weak world models. We study this agent-world-model gap by reproducing five visual world-model agents in Atari Pong: DreamerV3, DIAMOND,…
MotionPyramid: Hierarchical Motion Representation and Residual Interfaces
Gao Zhu, Zaishuo Xia, Yubei Chen
We ask whether the representational hierarchy seen in perception, from local primitives such as edges to higher level structures such as parts and objects, can be established for m…
Deep Networks Favor Simple Data
Weyl Lu, Chenjie Hao, Yubei Chen
Estimated density is often interpreted as indicating how typical a sample is under a model. Yet deep models trained on one dataset can assign higher density to simpler out-of-distr…
Alpha-RF: Automated RF-Filter-Circuit Design with Neural Simulator and Reinforcement Learning
Nhat Tran, Chenjie Hao, Alexander Stameroff +2
Accurate, high-performance radio-frequency (RF) filter circuits are ubiquitous in radio-frequency communication and sensing systems for accepting and rejecting signals at desired f…
When Models Know When They Do Not Know: Calibration, Cascading, and Cleaning
Chenjie Hao, Weyl Lu, Yuko Ishiwaka +3
When a model knows when it does not know, many possibilities emerge. The first question is how to enable a model to recognize that it does not know. A promising approach is to use…