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05/02/2023
Generalizing Dataset Distillation via Deep Generative Prior
Dataset Distillation aims to distill an entire dataset's knowledge into ...
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04/03/2023
Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning
In goal-reaching reinforcement learning (RL), the optimal value function...
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03/25/2023
Deep Augmentation: Enhancing Self-Supervised Learning through Transformations in Higher Activation Space
We introduce Deep Augmentation, an approach to data augmentation using d...
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02/22/2023
Steerable Equivariant Representation Learning
Pre-trained deep image representations are useful for post-training task...
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11/29/2022
Procedural Image Programs for Representation Learning
Learning image representations using synthetic data allows training neur...
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11/28/2022
Improved Representation of Asymmetrical Distances with Interval Quasimetric Embeddings
Asymmetrical distance structures (quasimetrics) are ubiquitous in our li...
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09/26/2022
Totems: Physical Objects for Verifying Visual Integrity
We introduce a new approach to image forensics: placing physical refract...
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06/30/2022
On the Learning and Learnablity of Quasimetrics
Our world is full of asymmetries. Gravity and wind can make reaching a p...
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06/30/2022
Denoised MDPs: Learning World Models Better Than the World Itself
The ability to separate signal from noise, and reason with clean abstrac...
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03/22/2022
Dataset Distillation by Matching Training Trajectories
Dataset distillation is the task of synthesizing a small dataset such th...
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06/10/2021
Learning to See by Looking at Noise
Current vision systems are trained on huge datasets, and these datasets ...
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07/30/2020
Rewriting a Deep Generative Model
A deep generative model such as a GAN learns to model a rich set of sema...
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06/18/2020
Diverse Image Generation via Self-Conditioned GANs
We introduce a simple but effective unsupervised method for generating r...
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05/20/2020
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
Contrastive representation learning has been outstandingly successful in...
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11/27/2018
Dataset Distillation
Model distillation aims to distill the knowledge of a complex model into...
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08/21/2017
Neural Block Sampling
Efficient Monte Carlo inference often requires manual construction of mo...
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08/10/2017
