30 citations · 63 across the 10 of their papers we have counts for
4 papers · 1 filter
Discrete-Valued Neural Communication
Dianbo Liu, Alex Lamb, Kenji Kawaguchi +4
Deep learning has advanced from fully connected architectures to structured models organized into components, e.g., the transformer composed of positional elements, modular archite…
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal +7
Inducing causal relationships from observations is a classic problem in machine learning. Most work in causality starts from the premise that the causal variables themselves are ob…
Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers
Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan +1
A discriminatively trained neural net classifier can fit the training data perfectly if all information about its input other than class membership has been discarded prior to the…
Improving Anytime Prediction with Parallel Cascaded Networks and a Temporal-Difference Loss
Michael L. Iuzzolino, Michael C. Mozer, Samy Bengio
Although deep feedforward neural networks share some characteristics with the primate visual system, a key distinction is their dynamics. Deep nets typically operate in serial stag…