Artur Dubrawski
37 papers · 2008–2025 · 10 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+10 more ↓ Show less ↑
🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (10) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏃 Academic Marathon (17)
🐣
Hot Topic Early Bird
🌉
Interdisciplinary Bridge
🌍
Conference Polyglot
(10)
🏆
Keyword Champion
🏆
Grand Slam
🗃️
Keyword Collector
(153)
📈
Trend Setter
💎
Century Club
(37)
🔥
Unstoppable
(11)
⚡
Prolific Year
(5)
Conferences
AAAI (10)
NIPS (8)
ICML (4)
MLHC (4)
ICLR (3)
AISTATS (2)
IJCAI (2)
JMLR (2)
CVPR (1)
UAI (1)
Top co-authors
Research topics
Keywords
semi-supervised learning
(6)
representation learning
(3)
dueling bandit
(3)
nonparametric regression
(2)
federated learning
(2)
weak supervision
(2)
ordinal information
(2)
curse of dimensionality
(2)
pairwise comparison
(2)
affective computing
(2)
latent variable model
(2)
cognitive state
(2)
text classification
(2)
time series classification
(2)
semi-supervised regression
(1)
feature learning
(1)
natural language processing
(1)
bayesian inference
(1)
dimensionality reduction
(1)
model combination
(1)
Papers
Exploring Representations and Interventions in Time Series Foundation Models
ICML 2025
MOMENT: A Family of Open Time-series Foundation Models
ICML 2024
JoLT: Jointly Learned Representations of Language and Time-Series for Clinical Time-Series Interpretation (Student Abstract)
AAAI 2024
Data-Driven Discovery of Design Specifications (Student Abstract)
AAAI 2024
PICSR: Prototype-Informed Cross-Silo Router for Federated Learning (Student Abstract)
AAAI 2024
Adapting Animal Models to Assess Sufficiency of Fluid Resuscitation in Humans (Student Abstract)
AAAI 2024
A Rate-Distortion View of Uncertainty Quantification
ICML 2024
Feature Learning for Interpretable, Performant Decision Trees
NIPS 2023
NHITS: Neural Hierarchical Interpolation for Time Series Forecasting
AAAI 2023
Ordinal Programmatic Weak Supervision and Crowdsourcing for Estimating Cognitive States (Student Abstract)
AAAI 2023
Generative Modeling Helps Weak Supervision (and Vice Versa)
ICLR 2023
AQuA: A Benchmarking Tool for Label Quality Assessment
NIPS 2023
Classifying Unstructured Clinical Notes via Automatic Weak Supervision
MLHC 2022
auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data
MLHC 2022
Actionable Model-Centric Explanations (Student Abstract)
AAAI 2022
Deep Attentive Variational Inference
ICLR 2022
End-to-End Weak Supervision
NIPS 2021
Understanding Clinical Collaborations Through Federated Classifier Selection
MLHC 2021
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling
ICLR 2021
Thresholding Bandit Problem with Both Duels and Pulls
AISTATS 2020
Preference-based Reinforcement Learning with Finite-Time Guarantees
NIPS 2020
Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information
JMLR 2020
Zeroth Order Non-convex optimization with Dueling-Choice Bandits
UAI 2020
Discriminating Cognitive Disequilibrium and Flow in Problem Solving: A Semi-Supervised Approach Using Involuntary Dynamic Behavioral Signals
AAAI 2020
Modeling Involuntary Dynamic Behaviors to Support Intelligent Tutoring (Student Abstract)
AAAI 2020
Robust Multi-View Representation Learning (Student Abstract)
AAAI 2020
On the Interaction Effects Between Prediction and Clustering
AISTATS 2019
Mutually Regressive Point Processes
NIPS 2019
Dynamically Personalized Detection of Hemorrhage
MLHC 2019
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information
ICML 2018
Noise-Tolerant Interactive Learning Using Pairwise Comparisons
NIPS 2017
Classification of Time Sequences using Graphs of Temporal Constraints
JMLR 2017
Scaling Active Search using Linear Similarity Functions
IJCAI 2017
VIPR: An Interactive Tool for Meaningful Visualization of High-Dimensional Data
IJCAI 2016
Real-Time Visual Analysis of Microvascular Blood Flow for Critical Care
CVPR 2015
Projection Retrieval for Classification
NIPS 2012
Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text
NIPS 2008