Daniel Jarrett
18 papers · 2019–2023 · 4 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (4) π Cross-Pollinator (9) π Interdisciplinary Bridge π§ Keyword Pioneer π Renaissance Researcher (8)
π
Renaissance Researcher
(8)
πΊοΈ
Taxonomy Completionist
(42)
π
Keyword Champion
π€
Dynamic Duo
(16)
π
Triple Crown
π
Century Club
(18)
π₯
Unstoppable
(5)
β‘
Prolific Year
(7)
ποΈ
Keyword Collector
(77)
Conferences
NIPS (8)
ICML (5)
ICLR (4)
AISTATS (1)
Top co-authors
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