research
∙
12/20/2022
Character-Aware Models Improve Visual Text Rendering
Current image generation models struggle to reliably produce well-formed...
share
research
∙
09/20/2022
Extremely Simple Activation Shaping for Out-of-Distribution Detection
The separation between training and deployment of machine learning model...
research
∙
09/07/2022
What does a platypus look like? Generating customized prompts for zero-shot image classification
Open vocabulary models are a promising new paradigm for image classifica...
research
∙
01/14/2022
When less is more: Simplifying inputs aids neural network understanding
How do neural network image classifiers respond to simpler and simpler i...
research
∙
11/07/2021
Natural Adversarial Objects
Although state-of-the-art object detection methods have shown compelling...
research
∙
09/16/2021
Language Models are Few-shot Multilingual Learners
General-purpose language models have demonstrated impressive capabilitie...
research
∙
07/16/2021
When does loss-based prioritization fail?
Not all examples are created equal, but standard deep neural network tra...
research
∙
07/05/2021
Why is Pruning at Initialization Immune to Reinitializing and Shuffling?
Recent studies assessing the efficacy of pruning neural networks methods...
research
∙
06/26/2020
Supermasks in Superposition
We present the Supermasks in Superposition (SupSup) model, capable of se...
research
∙
02/21/2020
Estimating Q(s,s') with Deep Deterministic Dynamics Gradients
In this paper, we introduce a novel form of value function, Q(s, s'), th...
research
∙
12/04/2019
Plug and Play Language Models: a Simple Approach to Controlled Text Generation
Large transformer-based language models (LMs) trained on huge text corpo...
research
∙
09/03/2019
LCA: Loss Change Allocation for Neural Network Training
Neural networks enjoy widespread use, but many aspects of their training...
research
∙
05/03/2019
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask
The recent "Lottery Ticket Hypothesis" paper by Frankle & Carbin showed ...
research
∙
12/17/2018
An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents
Much human and computational effort has aimed to improve how deep reinfo...
research
∙
07/09/2018
An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution
Few ideas have enjoyed as large an impact on deep learning as convolutio...
research
∙
04/24/2018