30 citations · 63 across the 10 of their papers we have counts for
5 papers · 1 filter
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers
Alex Lamb, Anirudh Goyal, Agnieszka Słowik +3
Feed-forward neural networks consist of a sequence of layers, in which each layer performs some processing on the information from the previous layer. A downside to this approach i…
Transforming Neural Network Visual Representations to Predict Human Judgments of Similarity
Maria Attarian, Brett D. Roads, Michael C. Mozer
Deep-learning vision models have shown intriguing similarities and differences with respect to human vision. We investigate how to bring machine visual representations into better…
Wandering Within a World: Online Contextualized Few-Shot Learning
Mengye Ren, Michael L. Iuzzolino, Michael C. Mozer +1
We aim to bridge the gap between typical human and machine-learning environments by extending the standard framework of few-shot learning to an online, continual setting. In this s…
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules
Sarthak Mittal, Alex Lamb, Anirudh Goyal +5
Robust perception relies on both bottom-up and top-down signals. Bottom-up signals consist of what's directly observed through sensation. Top-down signals consist of beliefs and ex…
Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems
Anirudh Goyal, Alex Lamb, Phanideep Gampa +5
Modeling a structured, dynamic environment like a video game requires keeping track of the objects and their states declarative knowledge) as well as predicting how objects behave…