research
∙
09/11/2023
Mind the Uncertainty: Risk-Aware and Actively Exploring Model-Based Reinforcement Learning
We introduce a simple but effective method for managing risk in model-ba...
share
research
∙
08/15/2023
Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World
Experimentation on real robots is demanding in terms of time and costs. ...
research
∙
07/28/2023
Benchmarking Offline Reinforcement Learning on Real-Robot Hardware
Learning policies from previously recorded data is a promising direction...
research
∙
07/21/2023
Diverse Offline Imitation via Fenchel Duality
There has been significant recent progress in the area of unsupervised s...
research
∙
06/14/2023
The ELM Neuron: an Efficient and Expressive Cortical Neuron Model Can Solve Long-Horizon Tasks
Traditional large-scale neuroscience models and machine learning utilize...
research
∙
06/12/2023
Locally adaptive cellular automata for goal-oriented self-organization
The essential ingredient for studying the phenomena of emergence is the ...
research
∙
06/07/2023
Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities
Unsupervised video-based object-centric learning is a promising avenue t...
research
∙
06/06/2023
Online Learning under Adversarial Nonlinear Constraints
In many applications, learning systems are required to process continuou...
research
∙
05/21/2023
Discovering Causal Relations and Equations from Data
Physics is a field of science that has traditionally used the scientific...
research
∙
04/21/2023
Minsight: A Fingertip-Sized Vision-Based Tactile Sensor for Robotic Manipulation
Intelligent interaction with the physical world requires perceptual abil...
research
∙
04/06/2023
Inductive biases in deep learning models for weather prediction
Deep learning has recently gained immense popularity in the Earth scienc...
research
∙
03/28/2023
When to be critical? Performance and evolvability in different regimes of neural Ising agents
It has long been hypothesized that operating close to the critical state...
research
∙
03/16/2023
Efficient Learning of High Level Plans from Play
Real-world robotic manipulation tasks remain an elusive challenge, since...
research
∙
09/16/2022
Versatile Skill Control via Self-supervised Adversarial Imitation of Unlabeled Mixed Motions
Learning diverse skills is one of the main challenges in robotics. To th...
research
∙
07/08/2022
Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks
Humans are able to outperform robots in terms of robustness, versatility...
research
∙
06/23/2022
Learning Agile Skills via Adversarial Imitation of Rough Partial Demonstrations
Learning agile skills is one of the main challenges in robotics. To this...
research
∙
06/22/2022
Curious Exploration via Structured World Models Yields Zero-Shot Object Manipulation
It has been a long-standing dream to design artificial agents that explo...
research
∙
06/06/2022
Embrace the Gap: VAEs Perform Independent Mechanism Analysis
Variational autoencoders (VAEs) are a popular framework for modeling com...
research
∙
06/04/2022
Developing hierarchical anticipations via neural network-based event segmentation
Humans can make predictions on various time scales and hierarchical leve...
research
∙
05/30/2022
Gradient Backpropagation Through Combinatorial Algorithms: Identity with Projection Works
Embedding discrete solvers as differentiable layers has given modern dee...
research
∙
05/30/2022
DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems
Muscle-actuated organisms are capable of learning an unparalleled divers...
research
∙
03/17/2022
On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks
Capturing aleatoric uncertainty is a critical part of many machine learn...
research
∙
12/06/2021
Hierarchical Reinforcement Learning with Timed Subgoals
Hierarchical reinforcement learning (HRL) holds great potential for samp...
research
∙
11/10/2021
A soft thumb-sized vision-based sensor with accurate all-round force perception
Vision-based haptic sensors have emerged as a promising approach to robo...
research
∙
10/29/2021
Sparsely Changing Latent States for Prediction and Planning in Partially Observable Domains
A common approach to prediction and planning in partially observable dom...
research
∙
10/12/2021
Planning from Pixels in Environments with Combinatorially Hard Search Spaces
The ability to form complex plans based on raw visual input is a litmus ...
research
∙
09/09/2021
Self-supervised Reinforcement Learning with Independently Controllable Subgoals
To successfully tackle challenging manipulation tasks, autonomous agents...
research
∙
06/07/2021
Causal Influence Detection for Improving Efficiency in Reinforcement Learning
Many reinforcement learning (RL) environments consist of independent ent...
research
∙
05/25/2021
Theory of Geometric Super-resolution for Haptic Sensor Design
Haptic feedback is important to make robots more dexterous and effective...
research
∙
05/18/2021
Assessing aesthetics of generated abstract images using correlation structure
Can we generate abstract aesthetic images without bias from natural or h...
research
∙
05/13/2021
Informed Equation Learning
Distilling data into compact and interpretable analytic equations is one...
research
∙
05/05/2021
CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints
Bridging logical and algorithmic reasoning with modern machine learning ...
research
∙
03/22/2021
The dynamical regime and its importance for evolvability, task performance and generalization
It has long been hypothesized that operating close to the critical state...
research
∙
02/15/2021
Neuro-algorithmic Policies enable Fast Combinatorial Generalization
Although model-based and model-free approaches to learning the control o...
research
∙
02/12/2021
Demystifying Inductive Biases for β-VAE Based Architectures
The performance of β-Variational-Autoencoders (β-VAEs) and their variant...
research
∙
12/28/2020
How to Train Your Differentiable Filter
In many robotic applications, it is crucial to maintain a belief about t...
research
∙
11/29/2020
Self-supervised Visual Reinforcement Learning with Object-centric Representations
Autonomous agents need large repertoires of skills to act reasonably on ...
research
∙
08/14/2020
Sample-efficient Cross-Entropy Method for Real-time Planning
Trajectory optimizers for model-based reinforcement learning, such as th...
research
∙
03/25/2020
Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers
Building on recent progress at the intersection of combinatorial optimiz...
research
∙
12/07/2019
Optimizing Rank-based Metrics with Blackbox Differentiation
Rank-based metrics are some of the most widely used criteria for perform...
research
∙
12/04/2019
Differentiation of Blackbox Combinatorial Solvers
Achieving fusion of deep learning with combinatorial algorithms promises...
research
∙
11/20/2019
Fast Non-Parametric Learning to Accelerate Mixed-Integer Programming for Online Hybrid Model Predictive Control
Today's fast linear algebra and numerical optimization tools have pushed...
research
∙
10/28/2019
Analytical classical density functionals from an equation learning network
We explore the feasibility of using machine learning methods to obtain a...
research
∙
06/19/2019
Control What You Can: Intrinsically Motivated Task-Planning Agent
We present a novel intrinsically motivated agent that learns how to cont...
research
∙
02/26/2019
Autonomous Identification and Goal-Directed Invocation of Event-Predictive Behavioral Primitives
Voluntary behavior of humans appears to be composed of small, elementary...
research
∙
12/17/2018
Variational Autoencoders Pursue PCA Directions (by Accident)
The Variational Autoencoder (VAE) is a powerful architecture capable of ...
research
∙
09/13/2018
Deep Reinforcement Learning for Event-Triggered Control
Event-triggered control (ETC) methods can achieve high-performance contr...
research
∙
06/19/2018
Learning Equations for Extrapolation and Control
We present an approach to identify concise equations from data using a s...
research
∙
10/10/2016
