Heinz Koeppl
36 papers · 2016–2026 · 11 conferences · across top CS/AI conferences
Achievements
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Keyword Pioneer
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Hot Topic Early Bird
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Academic Marathon
(9)
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Triple Crown
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Grand Slam
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Topic Evolution
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Keyword Champion
(3)
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Prolific Year
(10)
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Trend Setter
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Keyword Collector
(139)
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Century Club
(35)
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Unstoppable
(8)
Conferences
NIPS (9)
ICML (7)
AISTATS (5)
AAAI (3)
ACL (3)
ICLR (3)
JMLR (2)
EMNLP (1)
IJCAI (1)
NAACL (1)
UAI (1)
Top co-authors
Keywords
variational inference
(10)
mean field game
(4)
bayesian inference
(3)
continuous-time bayesian network
(3)
stochastic differential equation
(3)
switching dynamical system
(2)
deep reinforcement learning
(2)
continuous time
(2)
parameter inference
(2)
markov decision process
(2)
gibbs sampler
(2)
fictitious play
(2)
structure learning
(2)
markov jump process
(2)
inverse reinforcement learning
(2)
equilibrium learning
(2)
imitation learning
(2)
stochastic control
(2)
bounded rationality
(1)
approximate inference
(1)
Papers
CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval
ACL 2026
Entropic Matching for Expectation Propagation of Markov Jump Processes
AISTATS 2025
Bounded Rationality Equilibrium Learning in Mean Field Games
AAAI 2025
Learning Mean Field Control on Sparse Graphs
ICML 2025
Major-Minor Mean Field Multi-Agent Reinforcement Learning
ICML 2024
Approximate Control for Continuous-Time POMDPs
AISTATS 2024
MixGR: Enhancing Retriever Generalization for Scientific Domain through Complementary Granularity
EMNLP 2024
Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach
ICLR 2024
Graph Structure Inference with BAM: Neural Dependency Processing via Bilinear Attention
NIPS 2024
A Survey of Confidence Estimation and Calibration in Large Language Models
NAACL 2024
Learning Discrete-Time Major-Minor Mean Field Games
AAAI 2024
Negative-Binomial Randomized Gamma Dynamical Systems for Heterogeneous Overdispersed Count Time Sequences
IJCAI 2024
Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behavior
ICLR 2024
GeoHard: Towards Measuring Class-wise Hardness through Modelling Class Semantics
ACL 2024
ECOLA: Enhancing Temporal Knowledge Embeddings with Contextualized Language Representations
ACL 2023
Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs
NIPS 2023
Learning Sparse Graphon Mean Field Games
AISTATS 2023
Forward-Backward Latent State Inference for Hidden Continuous-Time semi-Markov Chains
NIPS 2022
Reinforcement Learning with Non-Exponential Discounting
NIPS 2022
Markov Chain Monte Carlo for Continuous-Time Switching Dynamical Systems
ICML 2022
Learning Graphon Mean Field Games and Approximate Nash Equilibria
ICLR 2022
Variational Inference for Continuous-Time Switching Dynamical Systems
NIPS 2021
Approximately Solving Mean Field Games via Entropy-Regularized Deep Reinforcement Learning
AISTATS 2021
Moment-Based Variational Inference for Stochastic Differential Equations
AISTATS 2021
Active Learning of Continuous-time Bayesian Networks through Interventions
ICML 2021
Continuous Time Bayesian Networks with Clocks
ICML 2020
POMDPs in Continuous Time and Discrete Spaces
NIPS 2020
The Hawkes Edge Partition Model for Continuous-time Event-based Temporal Networks
UAI 2020
A Variational Perturbative Approach to Planning in Graph-Based Markov Decision Processes
AAAI 2020
Correlation Priors for Reinforcement Learning
NIPS 2019
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
NIPS 2019
Moment-Based Variational Inference for Markov Jump Processes
ICML 2019
Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling
JMLR 2018
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
NIPS 2018
Dependent Relational Gamma Process Models for Longitudinal Networks
ICML 2018
A Variational Approach to Path Estimation and Parameter Inference of Hidden Diffusion Processes
JMLR 2016