← Authors

Ufuk Topcu

50 papers · 2012–2025 · 11 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (13) 🌈 Renaissance Researcher (5) 🐝 Cross-Pollinator (9) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (11) πŸ—ΊοΈ Taxonomy Completionist (18) πŸ”¬ Deep Specialist (11) 🧬 Topic Evolution πŸ† Grand Slam πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (201) πŸ“ˆ Trend Setter πŸ’Ž Century Club (50) πŸ”₯ Unstoppable (10) ⚑ Prolific Year (9)

Conferences

AAAI (10) IJCAI (10) UAI (5) ICML (4) L4DC (4) NIPS (4) RSS (4) ICLR (3) AISTATS (2) CORL (2) JMLR (2)

Top co-authors

Nils Jansen (8) Cyrus Neary (6) Franck Djeumou (6) Zhe Xu (5) Cevahir Koprulu (5) Abolfazl Hashemi (4) Min Wen (4) Steven Carr (4) Mahsa Ghasemi (4) Mustafa O. Karabag (3)

Research topics

Learning Paradigms (1) Learning Paradigms (1)

Keywords

temporal logic (10) markov decision process (8) reinforcement learning (6) dynamical system (4) policy learning (4) partially observable markov decision process (4) model-based reinforcement learning (3) neural ordinary differential equation (3) formal verification (3) sample complexity (3) model predictive control (3) physics-informed neural network (2) sequential decision (2) recurrent neural network (2) safe reinforcement learning (2) optimal control (2) policy optimization (2) sequential decision making (2) non-convex optimization (2) convex optimization (2)

Papers

Neural Stochastic Differential Equations for Uncertainty-Aware Offline RL ICLR 2025
Safety-Prioritizing Curricula for Constrained Reinforcement Learning ICLR 2025
CSA: Data-efficient Mapping of Unimodal Features to Multimodal Features ICLR 2025
Function Encoders: A Principled Approach to Transfer Learning in Hilbert Spaces ICML 2025
Categorical Semantics of Compositional Reinforcement Learning JMLR 2025
Dense Dynamics-Aware Reward Synthesis: Integrating Prior Experience with Demonstrations L4DC 2025
Sequential Decision Making in Stochastic Games with Incomplete Preferences over Temporal Objectives AAAI 2025
Human-Agent Cooperation in Games under Incomplete Information through Natural Language Communication IJCAI 2024
Zero-Shot Reinforcement Learning via Function Encoders ICML 2024
Accelerating Visual Sparse-Reward Learning with Latent Nearest-Demonstration-Guided Explorations CORL 2024
Zero-Shot Transfer of Neural ODEs NIPS 2024
On the Sample Complexity of Vanilla Model-Based Offline Reinforcement Learning with Dependent Samples AAAI 2023
Risk-aware curriculum generation for heavy-tailed task distributions UAI 2023
Task-aware Distributed Source Coding under Dynamic Bandwidth NIPS 2023
How to Learn and Generalize From Three Minutes of Data: Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential Equations CORL 2023
Learning Interpretable Temporal Properties from Positive Examples Only AAAI 2023
Compositional Learning of Dynamical System Models Using Port-Hamiltonian Neural Networks L4DC 2023
Safe Reinforcement Learning via Shielding under Partial Observability AAAI 2023
Reward-machine-guided, self-paced reinforcement learning UAI 2023
Differential Privacy in Cooperative Multiagent Planning UAI 2023
Class-Aware Adversarial Transformers for Medical Image Segmentation NIPS 2022
Faster non-convex federated learning via global and local momentum UAI 2022
Learning to Reach, Swim, Walk and Fly in One Trial: Data-Driven Control with Scarce Data and Side Information L4DC 2022
Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEs IJCAI 2022
Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling L4DC 2022
Robust Training in High Dimensions via Block Coordinate Geometric Median Descent AISTATS 2022
Deceptive Decision-Making under Uncertainty AAAI 2022
Smooth Convex Optimization Using Sub-Zeroth-Order Oracles AAAI 2021
Adaptive Teaching of Temporal Logic Formulas to Preference-based Learners AAAI 2021
Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks AAAI 2021
Advice-Guided Reinforcement Learning in a non-Markovian Environment AAAI 2021
Robust Finite-State Controllers for Uncertain POMDPs AAAI 2021
Algorithms for Fairness in Sequential Decision Making AISTATS 2021
Learning and Planning for Time-Varying MDPs Using Maximum Likelihood Estimation JMLR 2021
Safe Policies for Factored Partially Observable Stochastic Games RSS 2021
No-regret learning with high-probability in adversarial Markov decision processes UAI 2021
Task-Oriented Active Perception and Planning in Environments with Partially Known Semantics ICML 2020
Probabilistic Swarm Guidance Subject to Graph Temporal Logic Specifications RSS 2020
Verifiable RNN-Based Policies for POMDPs Under Temporal Logic Constraints IJCAI 2020
Robust Policy Synthesis for Uncertain POMDPs via Convex Optimization IJCAI 2020
Perception-Aware Point-Based Value Iteration for Partially Observable Markov Decision Processes IJCAI 2019
Transfer of Temporal Logic Formulas in Reinforcement Learning IJCAI 2019
Counterexample-Guided Strategy Improvement for POMDPs Using Recurrent Neural Networks IJCAI 2019
Submodular Observation Selection and Information Gathering for Quadratic Models ICML 2019
Constrained Cross-Entropy Method for Safe Reinforcement Learning NIPS 2018
Reduction Techniques for Model Checking and Learning in MDPs IJCAI 2017
Learning from Demonstrations with High-Level Side Information IJCAI 2017
Probably Approximately Correct Learning in Stochastic Games with Temporal Logic Specifications IJCAI 2016
Probably Approximately Correct MDP Learning and Control With Temporal Logic Constraints RSS 2014
Optimal Control with Weighted Average Costs and Temporal Logic Specifications RSS 2012