Search Results for author: Marin Vlastelica

Found 12 papers, 3 papers with code

Learning Diverse Skills for Local Navigation under Multi-constraint Optimality

no code implementations3 Oct 2023 Jin Cheng, Marin Vlastelica, Pavel Kolev, Chenhao Li, Georg Martius

We demonstrate the effectiveness of our method on a local navigation task where a quadruped robot needs to reach the target within a finite horizon.

Mind the Uncertainty: Risk-Aware and Actively Exploring Model-Based Reinforcement Learning

no code implementations11 Sep 2023 Marin Vlastelica, Sebastian Blaes, Cristina Pineri, Georg Martius

We introduce a simple but effective method for managing risk in model-based reinforcement learning with trajectory sampling that involves probabilistic safety constraints and balancing of optimism in the face of epistemic uncertainty and pessimism in the face of aleatoric uncertainty of an ensemble of stochastic neural networks. Various experiments indicate that the separation of uncertainties is essential to performing well with data-driven MPC approaches in uncertain and safety-critical control environments.

Model-based Reinforcement Learning reinforcement-learning

Diffusion Generative Inverse Design

no code implementations5 Sep 2023 Marin Vlastelica, Tatiana López-Guevara, Kelsey Allen, Peter Battaglia, Arnaud Doucet, Kimberley Stachenfeld

Inverse design refers to the problem of optimizing the input of an objective function in order to enact a target outcome.


Diverse Offline Imitation Learning

no code implementations21 Jul 2023 Marin Vlastelica, Jin Cheng, Georg Martius, Pavel Kolev

There has been significant recent progress in the area of unsupervised skill discovery, utilizing various information-theoretic objectives as measures of diversity.

D4RL Imitation Learning

Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to Harness Spurious Features

no code implementations19 Jul 2023 Cian Eastwood, Shashank Singh, Andrei Liviu Nicolicioiu, Marin Vlastelica, Julius von Kügelgen, Bernhard Schölkopf

To avoid failures on out-of-distribution data, recent works have sought to extract features that have an invariant or stable relationship with the label across domains, discarding "spurious" or unstable features whose relationship with the label changes across domains.

Backpropagation through Combinatorial Algorithms: Identity with Projection Works

2 code implementations30 May 2022 Subham Sekhar Sahoo, Anselm Paulus, Marin Vlastelica, Vít Musil, Volodymyr Kuleshov, Georg Martius

Embedding discrete solvers as differentiable layers has given modern deep learning architectures combinatorial expressivity and discrete reasoning capabilities.

Density Estimation Graph Matching +3

Taming Continuous Posteriors for Latent Variational Dialogue Policies

no code implementations16 May 2022 Marin Vlastelica, Patrick Ernst, György Szarvas

Utilizing amortized variational inference for latent-action reinforcement learning (RL) has been shown to be an effective approach in Task-oriented Dialogue (ToD) systems for optimizing dialogue success.

reinforcement-learning Reinforcement Learning (RL) +1

Neuro-algorithmic Policies enable Fast Combinatorial Generalization

no code implementations15 Feb 2021 Marin Vlastelica, Michal Rolínek, Georg Martius

Furthermore, we show that for a certain subclass of the MDP framework, this can be alleviated by neuro-algorithmic architectures.

Optimizing Rank-based Metrics with Blackbox Differentiation

1 code implementation7 Dec 2019 Michal Rolínek, Vít Musil, Anselm Paulus, Marin Vlastelica, Claudio Michaelis, Georg Martius

Rank-based metrics are some of the most widely used criteria for performance evaluation of computer vision models.

Image Retrieval object-detection +2

Differentiation of Blackbox Combinatorial Solvers

6 code implementations ICLR 2020 Marin Vlastelica, Anselm Paulus, Vít Musil, Georg Martius, Michal Rolínek

Achieving fusion of deep learning with combinatorial algorithms promises transformative changes to artificial intelligence.

Traveling Salesman Problem

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