Jost Tobias Springenberg
25 papers · 2014–2025 · 8 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (47) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Mega-Team Β· Squad
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Dynamic Duo
(17)
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Topic Evolution
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Keyword Pioneer
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Renaissance Researcher
(6)
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Unstoppable Β· Bronze
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Prolific Year Β· Productive
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Conference Pioneer
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Century Club Β· Bronze
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Trend Setter
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Keyword Collector
(119)
Top co-authors
Research topics
Machine Learning
(19)
Reinforcement Learning
(16)
Methods
(13)
Artificial Intelligence
(11)
Learning Types Β· Machine Learning
(9)
Applications
(8)
Optimization & Theory
(8)
Core AI
(7)
Deep Learning
(5)
Learning Paradigms
(5)
Core Methods
(4)
Robotics
(3)
Learning Types Β· Deep Learning
(3)
Computer Vision
(2)
Application Areas
(2)
Keywords
policy optimization
(7)
continuous control
(5)
offline reinforcement learning
(4)
transfer learning
(3)
reinforcement learning
(3)
off-policy learning
(3)
representation learning
(2)
data efficiency
(2)
multi-task learning
(2)
convolutional neural network
(2)
maximum a posteriori
(2)
hyperparameter optimization
(2)
robot manipulation
(2)
language model
(2)
deep reinforcement learning
(2)
online learning
(1)
image generation
(1)
sequence modeling
(1)
feature learning
(1)
model-based planning
(1)
Papers
Ο_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
NeurIPS 2024
Offline Actor-Critic Reinforcement Learning Scales to Large Models
ICML 2024
Evaluating Model-Based Planning and Planner Amortization for Continuous Control
ICLR 2022
Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes
CoRL 2021
Collect & Infer - a fresh look at data-efficient Reinforcement Learning
CoRL 2021
Compositional Transfer in Hierarchical Reinforcement Learning
RSS 2020
Critic Regularized Regression
NeurIPS 2020
Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning
ICLR 2020
Learning Dexterous Manipulation from Suboptimal Experts
CoRL 2020
Robust Reinforcement Learning for Continuous Control with Model Misspecification
ICLR 2020
Training Generative Adversarial Networks by Solving Ordinary Differential Equations
NeurIPS 2020
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control
ICLR 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
Graph Networks as Learnable Physics Engines for Inference and Control
ICML 2018
Learning an Embedding Space for Transferable Robot Skills
ICLR 2018
Learning by Playing Solving Sparse Reward Tasks from Scratch
ICML 2018
Maximum a Posteriori Policy Optimisation
ICLR 2018
Bayesian Optimization with Robust Bayesian Neural Networks
NeurIPS 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
NeurIPS 2014