← Authors

Daniel Jarrett

18 papers · 2019–2023 · 4 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (4) 🐝 Cross-Pollinator (9) 🌈 Renaissance Researcher (8) πŸ—ΊοΈ Taxonomy Completionist (42) πŸ† Keyword Champion 🀝 Dynamic Duo (16) πŸ‘‘ Triple Crown πŸ’Ž Century Club (18) πŸ”₯ Unstoppable (5) ⚑ Prolific Year (7) πŸ—ƒοΈ Keyword Collector (77)

Conferences

NIPS (8) ICML (5) ICLR (4) AISTATS (1)

Top co-authors

Mihaela van der Schaar (16) Alihan HΓΌyΓΌk (7) Ioana Bica (5) Jinsung Yoon (2) Ari Ercole (1) RΓ©mi Munos (1) Bogdan C Cebere (1) Corentin Tallec (1) Cem Tekin (1) Michal Valko (1)

Keywords

imitation learning (4) policy learning (4) time-series generation (2) hyperparameter optimization (2) sequence prediction (2) interpretable representation (2) deep kernel learning (1) online learning (1) policy evaluation (1) bounded rationality (1) model selection (1) trajectory modeling (1) temporal dynamics (1) distribution matching (1) resource allocation (1) generalization error (1) sequential decision (1) machine learning (1) domain generalization (1) offline reinforcement learning (1)

Papers

Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples NIPS 2023
Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments ICML 2023
AllSim: Simulating and Benchmarking Resource Allocation Policies in Multi-User Systems NIPS 2023
HyperImpute: Generalized Iterative Imputation with Automatic Model Selection ICML 2022
Inverse Contextual Bandits: Learning How Behavior Evolves over Time ICML 2022
Online Decision Mediation NIPS 2022
Closing the loop in medical decision support by understanding clinical decision-making: A case study on organ transplantation NIPS 2021
Learning "What-if" Explanations for Sequential Decision-Making ICLR 2021
Inverse Decision Modeling: Learning Interpretable Representations of Behavior ICML 2021
Time-series Generation by Contrastive Imitation NIPS 2021
Invariant Causal Imitation Learning for Generalizable Policies NIPS 2021
Clairvoyance: A Pipeline Toolkit for Medical Time Series ICLR 2021
Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning ICLR 2021
Target-Embedding Autoencoders for Supervised Representation Learning ICLR 2020
Strictly Batch Imitation Learning by Energy-based Distribution Matching NIPS 2020
Stepwise Model Selection for Sequence Prediction via Deep Kernel Learning AISTATS 2020
Inverse Active Sensing: Modeling and Understanding Timely Decision-Making ICML 2020
Time-series Generative Adversarial Networks NIPS 2019