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09/07/2022
Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes
Recent neuroimaging studies that focus on predicting brain disorders via...
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03/19/2022
The Sandbox Environment for Generalizable Agent Research (SEGAR)
A broad challenge of research on generalization for sequential decision-...
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01/12/2022
Robust Contrastive Learning against Noisy Views
Contrastive learning relies on an assumption that positive pairs contain...
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06/04/2021
Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL
A highly desirable property of a reinforcement learning (RL) agent – and...
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05/07/2021
Understanding by Understanding Not: Modeling Negation in Language Models
Negation is a core construction in natural language. Despite being very ...
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10/22/2020
Zero-Shot Learning from scratch (ZFS): leveraging local compositional representations
Zero-shot classification is a generalization task where no instance from...
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08/03/2020
Implicit Regularization in Deep Learning: A View from Function Space
We approach the problem of implicit regularization in deep learning from...
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07/27/2020
Representation Learning with Video Deep InfoMax
Self-supervised learning has made unsupervised pretraining relevant agai...
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07/12/2020
Data-Efficient Reinforcement Learning with Momentum Predictive Representations
While deep reinforcement learning excels at solving tasks where large am...
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06/12/2020
Deep Reinforcement and InfoMax Learning
Our work is based on the hypothesis that a model-free agent whose repres...
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03/16/2020
Object-Centric Image Generation from Layouts
Despite recent impressive results on single-object and single-domain ima...
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02/21/2020
An end-to-end approach for the verification problem: learning the right distance
In this contribution, we augment the metric learning setting by introduc...
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09/17/2019
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning
Continuous control tasks in reinforcement learning are important because...
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06/19/2019
Unsupervised State Representation Learning in Atari
State representation learning, or the ability to capture latent generati...
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06/03/2019
Learning Representations by Maximizing Mutual Information Across Views
We propose an approach to self-supervised representation learning based ...
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05/29/2019
Batch weight for domain adaptation with mass shift
Unsupervised domain transfer is the task of transferring or translating ...
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05/16/2019
Leveraging exploration in off-policy algorithms via normalizing flows
Exploration is a crucial component for discovering approximately optimal...
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04/24/2019
Prediction of Progression to Alzheimer`s disease with Deep InfoMax
Arguably, unsupervised learning plays a crucial role in the majority of ...
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04/12/2019
Spatio-Temporal Deep Graph Infomax
Spatio-temporal graphs such as traffic networks or gene regulatory syste...
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03/07/2019
Adversarial Mixup Resynthesizers
In this paper, we explore new approaches to combining information encode...
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09/27/2018
Deep Graph Infomax
We present Deep Graph Infomax (DGI), a general approach for learning nod...
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08/20/2018
Learning deep representations by mutual information estimation and maximization
Many popular representation-learning algorithms use training objectives ...
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07/31/2018
Online Adaptative Curriculum Learning for GANs
Generative Adversarial Networks (GANs) can successfully learn a probabil...
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01/12/2018
MINE: Mutual Information Neural Estimation
We argue that the estimation of the mutual information between high dime...
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11/13/2017
ACtuAL: Actor-Critic Under Adversarial Learning
Generative Adversarial Networks (GANs) are a powerful framework for deep...
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07/02/2017
Variance Regularizing Adversarial Learning
We introduce a novel approach for training adversarial models by replaci...
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02/27/2017
Boundary-Seeking Generative Adversarial Networks
We introduce a novel approach to training generative adversarial network...
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02/26/2017
Maximum-Likelihood Augmented Discrete Generative Adversarial Networks
Despite the successes in capturing continuous distributions, the applica...
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11/03/2016
Recurrent Neural Networks for Spatiotemporal Dynamics of Intrinsic Networks from fMRI Data
Functional magnetic resonance imaging (fMRI) of temporally-coherent bloo...
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03/21/2016
Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging Data
Independent component analysis (ICA), as an approach to the blind source...
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11/19/2015
