Elise van der Pol

Expected Return Symmetries

Tue, 04 Feb 2025 00:00:00 +0000

Our paper on Expected Return Symmetries was accepted to ICLR 2025. The paper concerns mutually incompatible symmetry breaking in zero-shot coordination. We introduce expected return symmetries, a broader symmetry class than environmental symmetries.

Symmetry & Structure in RL – State of the art, challenges, and future directions

Sat, 30 Nov 2024 00:00:00 +0000

30 November 2024 I gave a keynote at EWRL 2024

Talk

Fri, 29 Nov 2024 00:00:00 +0000

I gave a talk at the ChemAI workshop “Exploring Uncharted Paths: Mastering Retrosynthesis with Reinforcement Learning”.

Symmetry & Structure in RL - State of the art, challenges, and future directions

Mon, 14 Oct 2024 00:00:00 +0000

I gave a keynote at the IROS 2024 Workshop on Equivariant Robotics

Featured in CS PhD narratives book

Fri, 01 Dec 2023 00:00:00 +0000

I was featured in the PhD narratives book Why would I want to do a PhD in computer science?.

One-shot Imitation Learning via Interaction Warping

Mon, 06 Nov 2023 00:00:00 +0000

Symmetries in Single and Multi-Agent Learning

Wed, 25 Oct 2023 00:00:00 +0000

25th October 2023 I gave an invited talk at the Chalmers Structured Learning Workshop.

Symmetries in Reinforcement Learning

Tue, 10 Oct 2023 00:00:00 +0000

10th October 2023 I gave a talk at the WAI NL Summit.

Nomination for the WAI NL Researcher Award

Fri, 01 Sep 2023 00:00:00 +0000

I was nominated for the WAI NL Researcher Award.

Symmetry and Structure in Deep Reinforcement Learning

Wed, 12 Jul 2023 00:00:00 +0000

Successful PhD Defense

Wed, 12 Jul 2023 00:00:00 +0000

12th July 2023 I successfully defended my PhD thesis titled Symmetry and Structure in Deep Reinforcement Learning and obtained my PhD degree.

Organization: Symmetries in Robot Learning Workshop

Mon, 10 Jul 2023 00:00:00 +0000

We organized a workshop on Symmetries in Robot Learning at RSS 2023

Symmetries in Reinforcement Learning

Wed, 05 Jul 2023 00:00:00 +0000

5th July 2023 I gave a lecture on Symmetries in RL in the Barcelona Reinforcement Learning Summer School.

Physics for Machine Learning Workshop

Thu, 04 May 2023 00:00:00 +0000

We organized a workshop on Physics for Machine Learning at ICLR 2023.

Symmetry and Structure in Deep Reinforcement Learning

Thu, 02 Feb 2023 00:00:00 +0000

2nd February 2023 I gave an invited talk in the MILA Geometric Deep Learning Reading Group

WiML Profile

Mon, 23 Jan 2023 00:00:00 +0000

I was profiled by Women in Machine Learning.

Symmetry and Structure in Deep Reinforcement Learning

Wed, 14 Dec 2022 00:00:00 +0000

14 December 2022 I gave an invited talk at the icarl seminars at Imperial College London.

Introduction to Reinforcement Learning

Fri, 09 Dec 2022 00:00:00 +0000

I gave a guest lecture Introduction to Reinforcement Learning in University of Amsterdam’s MSc Data Science course Applied Machine Learning.

Maximum Class Separation as Inductive Bias in One Matrix

Mon, 28 Nov 2022 00:00:00 +0000

Equivariant Networks for Zero-Shot Coordination

Mon, 28 Nov 2022 00:00:00 +0000

Stochastic Parallelizable Eigengap Dilation for Large Graph Clustering

Fri, 22 Jul 2022 00:00:00 +0000

Based on some work we did during my DeepMind internship.

Symmetries in Reinforcement Learning

Thu, 14 Jul 2022 00:00:00 +0000

14th July 2022 I’m giving a lecture on Symmetries in Reinforcement Learning at the Amsterdam Reinforcement Learning Summer School.

Symmetry and Structure in Deep Reinforcement Learning

Fri, 03 Jun 2022 00:00:00 +0000

03 June 2022 I gave an invited talk at BeneRL 2022.

Microsoft Senior Researcher

Sun, 01 May 2022 00:00:00 +0000

I’ve joined Microsoft Research Amsterdam as a Senior Researcher. I’ll be working on reinforcement learning and deep learning for molecular simulation.

Gamification and Multi-Agent Solutions Workshop

Fri, 29 Apr 2022 00:00:00 +0000

We organized a workshop on gamification and multi-agent solutions at ICLR 2022.

Multi-Agent MDP Homomorphic Networks

Mon, 25 Apr 2022 00:00:00 +0000

Geometric and Physical Quantities improve E(3) Equivariant Message Passing

Mon, 25 Apr 2022 00:00:00 +0000

Symmetry and Structure in Deep Reinforcement Learning

Tue, 19 Apr 2022 00:00:00 +0000

19 April 2022 I gave an invited talk at University of Oxford.

Data-Centric Reinforcement Learning Workshop

Tue, 14 Dec 2021 00:00:00 +0000

We organized a workshop on data-centric reinforcement learning at NeurIPS 2021.

Introduction to Reinforcement Learning

Tue, 30 Nov 2021 00:00:00 +0000

30 November 2021 I gave a guest lecture Introduction to Reinforcement Learning in University of Amsterdam’s MSc Data Science course Applied Machine Learning.

The Impact of Negative Sampling on Contrastive Structured World Models

Sat, 24 Jul 2021 00:00:00 +0000

Authors

O. Biza, E. van der Pol, T. Kipf

Venue

ICML 2021 workshop on Self-Supervised Learning for Reasoning and Perception

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Other

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Geometric Deep Learning and Reinforcement Learning

Thu, 15 Jul 2021 00:00:00 +0000

15 July 2021 I gave a talk on Geometric Deep Learning and Reinforcement Learning for the Geometric Deep Learning course in the African Masters in Machine Intelligence.

DeepMind Internship

Tue, 01 Jun 2021 00:00:00 +0000

I was a research scientist intern in DeepMind’s Multi-Agent team.

Equivariance in MDPs

Fri, 07 May 2021 00:00:00 +0000

7 May 2021 I gave a keynote talk on Equivariance in MDPs at the ICLR workshop on Self-supervision for Reinforcement Learning.

Bad Hypothesis Contest Social

Thu, 06 May 2021 00:00:00 +0000

We organized an ICLR social which took place 6 May 2021.

Featured in GNNs in RL blog

Thu, 21 Jan 2021 00:00:00 +0000

I was invited to contribute my thoughts on GNNs in RL to What does 2022 hold for Geometric and Graph ML? by Michael Bronstein and Petar Veličkovi

MDP Homomorphic Networks for Deep Reinforcement Learning

Tue, 15 Dec 2020 00:00:00 +0000

15 December 2020 I gave a talk on MDP Homomorphic Networks for Deep Reinforcement Learning at the University of Tuebingen.

MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning

Sun, 06 Dec 2020 00:00:00 +0000

Introduction to Reinforcement Learning

Mon, 23 Nov 2020 00:00:00 +0000

23 November 2020 I gave a guest lecture Introduction to Reinforcement Learning in University of Amsterdam’s MSc Data Science course Applied Machine Learning.

Equivariance, deep reinforcement learning, and making it work

Fri, 13 Nov 2020 00:00:00 +0000

13 November 2020 I gave a talk on Equivariance, deep reinforcement learning, and making it work at Leiden University.

Data-Efficient Reinforcement Learning

Sun, 18 Oct 2020 00:00:00 +0000

I gave a talk on Data-efficient Reinforcement Learning as part of TU Delft’s AI in Practice course.

Plannable Approximations to MDP Homomorphisms: Equivariance under Actions

Sat, 09 May 2020 00:00:00 +0000

Contrastive Learning of Structured World Models

Sun, 26 Apr 2020 00:00:00 +0000

Hyperspherical Prototype Networks

Sun, 08 Dec 2019 00:00:00 +0000

Hyperspherical Prototype Networks

Mon, 28 Oct 2019 00:00:00 +0000

Introduction to Reinforcement Learning

Mon, 19 Nov 2018 00:00:00 +0000

Deep Latent Planning

Mon, 19 Nov 2018 00:00:00 +0000

Visual Rationalizations in Deep Reinforcement Learning for Atari Games

Thu, 08 Nov 2018 00:00:00 +0000

Paper on post-hoc explanations in deep reinforcement learning, based on Laurens Weitkamp’s BSc thesis.

Beyond Local Nash Equilibria for Adversarial Networks

Thu, 08 Nov 2018 00:00:00 +0000

GANGs: Generative Adversarial Network Games

Sat, 02 Dec 2017 00:00:00 +0000

Coordinated Deep Reinforcement Learners for Traffic Light Control

Fri, 09 Dec 2016 00:00:00 +0000

Video Demo: Deep Reinforcement Learning for Coordination in Traffic Light Control

Thu, 10 Nov 2016 00:00:00 +0000

Deep Reinforcement Learning for Coordination in Traffic Light Control

Mon, 29 Aug 2016 00:00:00 +0000

Linguistic Style Accommodation in Disagreements

Thu, 11 Aug 2016 00:00:00 +0000

Deep Reinforcement Learning

Mon, 23 May 2016 00:00:00 +0000

Empirical Evaluation of Collective Rationality for Quota Rules in Judgment Aggregation

Thu, 05 Nov 2015 00:00:00 +0000