research
∙
07/06/2023
Focused Transformer: Contrastive Training for Context Scaling
Large language models have an exceptional capability to incorporate new ...
share
research
∙
05/31/2023
The Tunnel Effect: Building Data Representations in Deep Neural Networks
Deep neural networks are widely known for their remarkable effectiveness...
research
∙
03/27/2023
Exploring Continual Learning of Diffusion Models
Diffusion models have achieved remarkable success in generating high-qua...
research
∙
03/08/2023
Magnushammer: A Transformer-based Approach to Premise Selection
Premise selection is a fundamental problem of automated theorem proving....
research
∙
11/29/2022
The Surprising Effectiveness of Latent World Models for Continual Reinforcement Learning
We study the use of model-based reinforcement learning methods, in parti...
research
∙
11/24/2022
Trust Your ∇: Gradient-based Intervention Targeting for Causal Discovery
Inferring causal structure from data is a challenging task of fundamenta...
research
∙
09/28/2022
Disentangling Transfer in Continual Reinforcement Learning
The ability of continual learning systems to transfer knowledge from pre...
research
∙
06/01/2022
Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
Complex reasoning problems contain states that vary in the computational...
research
∙
05/22/2022
Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers
In theorem proving, the task of selecting useful premises from a large l...
research
∙
11/30/2021
Continuous Control With Ensemble Deep Deterministic Policy Gradients
The growth of deep reinforcement learning (RL) has brought multiple exci...
research
∙
11/22/2021
Off-Policy Correction For Multi-Agent Reinforcement Learning
Multi-agent reinforcement learning (MARL) provides a framework for probl...
research
∙
11/11/2021
Catalytic Role Of Noise And Necessity Of Inductive Biases In The Emergence Of Compositional Communication
Communication is compositional if complex signals can be represented as ...
research
∙
08/25/2021
Subgoal Search For Complex Reasoning Tasks
Humans excel in solving complex reasoning tasks through a mental process...
research
∙
05/23/2021
Continual World: A Robotic Benchmark For Continual Reinforcement Learning
Continual learning (CL) – the ability to continuously learn, building on...
research
∙
02/12/2021
Robust and Efficient Planning using Adaptive Entropy Tree Search
In this paper, we present the Adaptive EntropyTree Search (ANTS) algorit...
research
∙
12/16/2020
CARLA Real Traffic Scenarios – novel training ground and benchmark for autonomous driving
This work introduces interactive traffic scenarios in the CARLA simulato...
research
∙
12/19/2019
Uncertainty-sensitive Learning and Planning with Ensembles
We propose a reinforcement learning framework for discrete environments ...
research
∙
11/29/2019
Simulation-based reinforcement learning for real-world autonomous driving
We use synthetic data and a reinforcement learning algorithm to train a ...
research
∙
10/04/2019
Developmentally motivated emergence of compositional communication via template transfer
This paper explores a novel approach to achieving emergent compositional...
research
∙
03/01/2019
Model-Based Reinforcement Learning for Atari
Model-free reinforcement learning (RL) can be used to learn effective po...
research
∙
09/10/2018
Expert-augmented actor-critic for ViZDoom and Montezumas Revenge
We propose an expert-augmented actor-critic algorithm, which we evaluate...
research
∙
04/02/2018
