Anna Goldenberg
18 papers · 2018–2026 · 8 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (7) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (8) 🐝 Cross-Pollinator (14)
🏃
Academic Marathon
(7)
🧭
Keyword Pioneer
🐝
Cross-Pollinator
(14)
🏆
Keyword Champion
(2)
🔥
Unstoppable
(5)
💎
Century Club
(17)
❓
The Questioner
🗃️
Keyword Collector
(60)
Conferences
MLHC (7)
ICLR (4)
MIDL (2)
AISTATS (1)
CVPR (1)
ICML (1)
NIPS (1)
UAI (1)
Top co-authors
Keywords
clinical practice
(2)
recurrent neural network
(2)
time series
(2)
representation learning
(1)
off-policy evaluation
(1)
domain generalization
(1)
contrastive learning
(1)
ensemble learning
(1)
data augmentation
(1)
kl divergence
(1)
multimodal learning
(1)
feature importance
(1)
clinical prediction
(1)
time series classification
(1)
mutual information
(1)
domain adaptation
(1)
machine learning
(1)
distribution shift
(1)
stochastic process
(1)
image classification
(1)
Papers
Unpaired Multimodal Learning for Biological Datasets
MIDL 2026
Learning under Temporal Label Noise
ICLR 2025
HDP-Flow: Generalizable Bayesian Nonparametric Model for Time Series State Discovery
UAI 2025
Needles in Needle Stacks: Meaningful Clinical Information Buried in Noisy Sensor Data
MLHC 2024
Improving Identically Distributed and Out-of-Distribution Medical Image Classification with Segmentation-Guided Attention in Small Dataset Scenarios
MIDL 2024
NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning
ICLR 2022
Decoupling Local and Global Representations of Time Series
AISTATS 2022
Error Amplification When Updating Deployed Machine Learning Models
MLHC 2022
Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding
ICLR 2021
Towards Robust Classification Model by Counterfactual and Invariant Data Generation
CVPR 2021
What went wrong and when? Instance-wise feature importance for time-series black-box models
NIPS 2020
Hidden Risks of Machine Learning Applied to Healthcare: Unintended Feedback Loops Between Models and Future Data Causing Model Degradation
MLHC 2020
Preparing a Clinical Support Model for Silent Mode in General Internal Medicine
MLHC 2020
Explaining Image Classifiers by Counterfactual Generation
ICLR 2019
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use
MLHC 2019
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks
MLHC 2019
Dynamic Measurement Scheduling for Event Forecasting using Deep RL
ICML 2019
Prediction of Cardiac Arrest from Physiological Signals in the Pediatric ICU
MLHC 2018