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01/18/2023
Human-Timescale Adaptation in an Open-Ended Task Space
Foundation models have shown impressive adaptation and scalability in su...
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01/19/2021
Self-Organizing Intelligent Matter: A blueprint for an AI generating algorithm
We propose an artificial life framework aimed at facilitating the emerge...
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03/06/2020
Finding online neural update rules by learning to remember
We investigate learning of the online local update rules for neural acti...
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02/07/2020
Causally Correct Partial Models for Reinforcement Learning
In reinforcement learning, we can learn a model of future observations a...
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06/21/2019
Shaping Belief States with Generative Environment Models for RL
When agents interact with a complex environment, they must form and main...
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01/11/2019
An investigation of model-free planning
The field of reinforcement learning (RL) is facing increasingly challeng...
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11/23/2018
Learning Attractor Dynamics for Generative Memory
A central challenge faced by memory systems is the robust retrieval of a...
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06/08/2018
Temporal Difference Variational Auto-Encoder
One motivation for learning generative models of environments is to use ...
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02/08/2018
Learning and Querying Fast Generative Models for Reinforcement Learning
A key challenge in model-based reinforcement learning (RL) is to synthes...
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11/22/2016
Variational Intrinsic Control
In this paper we introduce a new unsupervised reinforcement learning met...
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06/05/2016
What is the Best Feature Learning Procedure in Hierarchical Recognition Architectures?
(This paper was written in November 2011 and never published. It is post...
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05/07/2016
Neural Autoregressive Distribution Estimation
We present Neural Autoregressive Distribution Estimation (NADE) models, ...
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04/29/2016
Towards Conceptual Compression
We introduce a simple recurrent variational auto-encoder architecture th...
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03/16/2016
One-Shot Generalization in Deep Generative Models
Humans have an impressive ability to reason about new concepts and exper...
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11/19/2015
Towards Principled Unsupervised Learning
General unsupervised learning is a long-standing conceptual problem in m...
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02/16/2015
DRAW: A Recurrent Neural Network For Image Generation
This paper introduces the Deep Recurrent Attentive Writer (DRAW) neural ...
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02/12/2015
MADE: Masked Autoencoder for Distribution Estimation
There has been a lot of recent interest in designing neural network mode...
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01/31/2014
Neural Variational Inference and Learning in Belief Networks
Highly expressive directed latent variable models, such as sigmoid belie...
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02/28/2012
Fast approximations to structured sparse coding and applications to object classification
We describe a method for fast approximation of sparse coding. The input ...
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08/04/2011
Learning Representations by Maximizing Compression
We give an algorithm that learns a representation of data through compre...
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05/26/2011
Efficient Learning of Sparse Invariant Representations
We propose a simple and efficient algorithm for learning sparse invarian...
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12/03/2009