Vitaly Kurin | DeepAI

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∙ 09/22/2022

A Generalist Neural Algorithmic Learner

The cornerstone of neural algorithmic reasoning is the ability to solve ...

6 Borja Ibarz, et al. ∙

∙ 03/22/2022

Insights From the NeurIPS 2021 NetHack Challenge

In this report, we summarize the takeaways from the first NeurIPS 2021 N...

9 Eric Hambro, et al. ∙

∙ 01/31/2022

You May Not Need Ratio Clipping in PPO

Proximal Policy Optimization (PPO) methods learn a policy by iteratively...

0 Mingfei Sun, et al. ∙

∙ 01/11/2022

In Defense of the Unitary Scalarization for Deep Multi-Task Learning

Recent multi-task learning research argues against unitary scalarization...

0 Vitaly Kurin, et al. ∙

∙ 09/27/2021

MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research

The progress in deep reinforcement learning (RL) is heavily driven by th...

7 Mikayel Samvelyan, et al. ∙

∙ 03/01/2021

Snowflake: Scaling GNNs to High-Dimensional Continuous Control via Parameter Freezing

Recent research has shown that Graph Neural Networks (GNNs) can learn po...

8 Charlie Blake, et al. ∙

∙ 10/05/2020

My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

Multitask Reinforcement Learning is a promising way to obtain models wit...

7 Vitaly Kurin, et al. ∙

∙ 09/27/2019

Deep Coordination Graphs

This paper introduces the deep coordination graph (DCG) for collaborativ...

54 Wendelin Böhmer, et al. ∙

∙ 09/26/2019

Improving SAT Solver Heuristics with Graph Networks and Reinforcement Learning

We present GQSAT, a branching heuristic in a Boolean SAT solver trained ...

37 Vitaly Kurin, et al. ∙

∙ 02/18/2019

Fast Efficient Hyperparameter Tuning for Policy Gradients

The performance of policy gradient methods is sensitive to hyperparamete...

20 Supratik Paul, et al. ∙

∙ 11/08/2018

Learning from Demonstration in the Wild

Learning from demonstration (LfD) is useful in settings where hand-codin...

8 Feryal Behbahani, et al. ∙

∙ 10/08/2018

CAML: Fast Context Adaptation via Meta-Learning

We propose CAML, a meta-learning method for fast adaptation that partiti...

2 Luisa M Zintgraf, et al. ∙

∙ 05/31/2017

The Atari Grand Challenge Dataset

Recent progress in Reinforcement Learning (RL), fueled by its combinatio...

0 Vitaly Kurin, et al. ∙

∙ 05/12/2017

Towards a Principled Integration of Multi-Camera Re-Identification and Tracking through Optimal Bayes Filters

With the rise of end-to-end learning through deep learning, person detec...

0 Lucas Beyer, et al. ∙

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