Wilko Schwarting

14 papers · 2020–2024 · 5 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🐣 Hot Topic Early Bird 🗺️ Taxonomy Completionist (29) 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🤝 Dynamic Duo (12)

🗃️ Keyword Collector (69) 🚀 Conference Pioneer 🔥 Unstoppable · Bronze ❓ The Questioner 💎 Century Club · Bronze 🌈 Renaissance Researcher (5)

Venues

L4DC (5) CoRL (4) ICLR (2) NeurIPS (2) WACV (1)

Top co-authors

Daniela Rus (12) Tim Seyde (9) Igor Gilitschenski (7) Sertac Karaman (6) Markus Wulfmeier (4) Peter Werner (3) Chris Baker (2) Ryan Sander (2) Martin Riedmiller (2) Alexander Amini (2)

Research topics

Machine Learning (10) Reinforcement Learning (9) Methods (8) Artificial Intelligence (7) Core AI (6) Applications (5) Optimization & Theory (5) Learning Types (4) Computer Vision (2) Robotics (2) Analysis (2) Core Methods (2) Deep Learning (1) Mathematics & Optimization (1) Application Areas (1)

Keywords

continuous control (5) uncertainty quantification (2) neural network (2) multi-agent reinforcement learning (2) deep reinforcement learning (2) model-based reinforcement learning (2) upper confidence bound (2) value decomposition (2) pose estimation (1) epistemic uncertainty (1) sim-to-real transfer (1) point cloud registration (1) motion estimation (1) autonomous driving (1) hyperparameter optimization (1) imitation learning (1) value function (1) optimal control (1) policy gradient (1) constrained optimization (1)

Papers

Do no harm: A counterfactual approach to safe reinforcement learning L4DC 2024 Growing Q-networks: Solving continuous control tasks with adaptive control resolution L4DC 2024 OptFlow: Fast Optimization-Based Scene Flow Estimation Without Supervision WACV 2024 Dynamic Multi-Team Racing: Competitive Driving on 1/10-th Scale Vehicles via Learning in Simulation CoRL 2023 Solving Continuous Control via Q-learning ICLR 2023 Deep Interactive Motion Prediction and Planning: Playing Games with Motion Prediction Models L4DC 2022 Neighborhood Mixup Experience Replay: Local Convex Interpolation for Improved Sample Efficiency in Continuous Control Tasks L4DC 2022 Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies NeurIPS 2021 Learning to Plan Optimistically: Uncertainty-Guided Deep Exploration via Latent Model Ensembles CoRL 2021 Strength Through Diversity: Robust Behavior Learning via Mixture Policies CoRL 2021 Deep Evidential Regression NeurIPS 2020 Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space CoRL 2020 Deep Orientation Uncertainty Learning based on a Bingham Loss ICLR 2020 Learning to Plan via Deep Optimistic Value Exploration L4DC 2020