14 citations · 81 across the 16 of their papers we have counts for
15 papers · 1 filter
When Geometry Aligns: Dihedral Hidden-State Transformations in UNet, ViT, and DiT Architectures
Mojtaba Faramarzi, Alex Lamb, Irina Rish
Diffusion architectures now encompass convolutional UNets as well as transformer-based designs such as Diffusion Transformers (DiTs), inspired by Vision Transformers (ViTs), yet th…
Towards Data-Driven Offline Simulations for Online Reinforcement Learning
Shengpu Tang, Felipe Vieira Frujeri, Dipendra Misra +4
Modern decision-making systems, from robots to web recommendation engines, are expected to adapt: to user preferences, changing circumstances or even new tasks. Yet, it is still un…
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning
Riashat Islam, Hongyu Zang, Anirudh Goyal +6
Goal-conditioned reinforcement learning (RL) is a promising direction for training agents that are capable of solving multiple tasks and reach a diverse set of objectives. How to \…
CNT (Conditioning on Noisy Targets): A new Algorithm for Leveraging Top-Down Feedback
Alexia Jolicoeur-Martineau, Alex Lamb, Vikas Verma +1
We propose a novel regularizer for supervised learning called Conditioning on Noisy Targets (CNT). This approach consists in conditioning the model on a noisy version of the target…
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization
Dianbo Liu, Alex Lamb, Xu Ji +4
Vector Quantization (VQ) is a method for discretizing latent representations and has become a major part of the deep learning toolkit. It has been theoretically and empirically sho…
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…