← Authors

Jost Tobias Springenberg

25 papers · 2014–2025 · 8 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (13) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (38) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌈 Renaissance Researcher (8) 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (11) 🀝 Dynamic Duo (17) πŸ‘₯ Mega-Team (35) 🧬 Topic Evolution πŸ’Ž Century Club (25) πŸ“ˆ Trend Setter ⚑ Prolific Year (7) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (79) πŸ”₯ Unstoppable (5)

Conferences

ICLR (7) CORL (5) NIPS (5) ICML (3) RSS (2) AUTOML (1) CVPR (1) IJCAI (1)

Top co-authors

Martin Riedmiller (17) Nicolas Heess (14) Abbas Abdolmaleki (11) Thomas Lampe (8) Roland Hafner (7) Michael Neunert (6) Noah Siegel (4) Arunkumar Byravan (3) Francesco Nori (3) Michael Bloesch (3)

Keywords

offline reinforcement learning (4) policy optimization (3) off-policy learning (2) reinforcement learning (2) hyperparameter optimization (2) transfer learning (2) robot manipulation (2) convolutional neural network (2) multi-task learning (2) representation learning (2) image classification (1) image generation (1) online learning (1) imitation learning (1) sequence modeling (1) sequence generation (1) feature learning (1) ensemble learning (1) robotic manipulation (1) 3d reconstruction (1)

Papers

$\pi_0.5$: a Vision-Language-Action Model with Open-World Generalization CORL 2025
Learning from negative feedback, or positive feedback or both ICLR 2025
Imitating Language via Scalable Inverse Reinforcement Learning NIPS 2024
Offline Actor-Critic Reinforcement Learning Scales to Large Models ICML 2024
Evaluating Model-Based Planning and Planner Amortization for Continuous Control ICLR 2022
Collect & Infer - a fresh look at data-efficient Reinforcement Learning CORL 2021
Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes CORL 2021
Robust Reinforcement Learning for Continuous Control with Model Misspecification ICLR 2020
Training Generative Adversarial Networks by Solving Ordinary Differential Equations NIPS 2020
Critic Regularized Regression NIPS 2020
Learning Dexterous Manipulation from Suboptimal Experts CORL 2020
Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning ICLR 2020
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control ICLR 2020
Compositional Transfer in Hierarchical Reinforcement Learning RSS 2020
Imagined Value Gradients: Model-Based Policy Optimization with Tranferable Latent Dynamics Models CORL 2019
Simultaneously Learning Vision and Feature-Based Control Policies for Real-World Ball-In-A-Cup RSS 2019
Maximum a Posteriori Policy Optimisation ICLR 2018
Learning an Embedding Space for Transferable Robot Skills ICLR 2018
Learning by Playing Solving Sparse Reward Tasks from Scratch ICML 2018
Graph Networks as Learnable Physics Engines for Inference and Control ICML 2018
Bayesian Optimization with Robust Bayesian Neural Networks NIPS 2016
Towards Automatically-Tuned Neural Networks AUTOML 2016
Learning to Generate Chairs With Convolutional Neural Networks CVPR 2015
Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves IJCAI 2015
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks NIPS 2014