research
∙
05/07/2023
Leveraging Synthetic Targets for Machine Translation
In this work, we provide a recipe for training machine translation model...
share
research
∙
12/27/2022
MixupE: Understanding and Improving Mixup from Directional Derivative Perspective
Mixup is a popular data augmentation technique for training deep neural ...
research
∙
10/25/2022
From Points to Functions: Infinite-dimensional Representations in Diffusion Models
Diffusion-based generative models learn to iteratively transfer unstruct...
research
∙
06/09/2022
On Neural Architecture Inductive Biases for Relational Tasks
Current deep learning approaches have shown good in-distribution general...
research
∙
06/06/2022
Is a Modular Architecture Enough?
Inspired from human cognition, machine learning systems are gradually re...
research
∙
10/18/2021
Compositional Attention: Disentangling Search and Retrieval
Multi-head, key-value attention is the backbone of the widely successful...
research
∙
07/02/2021
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
Inducing causal relationships from observations is a classic problem in ...
research
∙
06/30/2020
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules
Robust perception relies on both bottom-up and top-down signals. Bottom-...
research
∙
10/19/2018