Uri Shalit

发表

Deep Kalman Filters pdf

Uri Shalit, David Sontag, Rahul G. Krishnan, 2015, ArXiv.

Large Scale Online Learning of Image Similarity Through Ranking

Samy Bengio, Varun Sharma, Gal Chechik, 2009, J. Mach. Learn. Res..

Bounding and Minimizing Counterfactual Error pdf

Uri Shalit, David Sontag, Fredrik D. Johansson, 2016, ArXiv.

Estimating individual treatment effect: generalization bounds and algorithms

Uri Shalit, David Sontag, Fredrik D. Johansson, 2016, ICML.

Learning Weighted Representations for Generalization Across Designs

Fredrik D. Johansson, D. Sontag, Uri Shalit, 2018, 1802.08598.

Structured Inference Networks for Nonlinear State Space Models

Uri Shalit, David Sontag, Rahul G. Krishnan, 2016, AAAI.

An Online Algorithm for Large Scale Image Similarity Learning

Samy Bengio, Varun Sharma, Gal Chechik, 2009, NIPS.

Large Scale Online Learning of Image Similarity through Ranking

Samy Bengio, Varun Sharma, Gal Chechik, 2009, IbPRIA.

Modeling Musical Influence with Topic Models

Daphna Weinshall, Gal Chechik, Uri Shalit, 2013, ICML.

Learning Representations for Counterfactual Inference pdf

Uri Shalit, David Sontag, Fredrik D. Johansson, 2016, ICML.

Causal Effect Inference with Deep Latent-Variable Models

Max Welling, Joris M. Mooij, Richard S. Zemel, 2017, NIPS 2017.

Coordinate-descent for learning orthogonal matrices through Givens rotations

Gal Chechik, Uri Shalit, Gal Chechik, 2014, ICML.

Online Learning in The Manifold of Low-Rank Matrices

Daphna Weinshall, Gal Chechik, Uri Shalit, 2010, NIPS.

A causal view of compositional zero-shot recognition

Gal Chechik, Uri Shalit, Y. Atzmon, 2020, NeurIPS.

Descending systems translate transient cortical commands into a sustained muscle activation signal.

Uri Shalit, Yifat Prut, Mati Joshua, 2012, Cerebral cortex.

Scalable Sensitivity and Uncertainty Analysis for Causal-Effect Estimates of Continuous-Valued Interventions

N. Meinshausen, Y. Gal, Uri Shalit, 2022, ArXiv.

Computation in spinal circuitry: Lessons from behaving primates

Uri Shalit, Yuval Yanai, Zvi Israel, 2008, Behavioural Brain Research.

Developing a COVID-19 mortality risk prediction model when individual-level data are not available

G. Rothblum, Uri Shalit, R. Balicer, 2020, Nature Communications.

Performing risk stratification for COVID-19 when individual level data is not available, the experience of a large healthcare organization

G. Rothblum, Uri Shalit, R. Balicer, 2020, medRxiv.

Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding pdf

Uri Shalit, Yarin Gal, Andrew Jesson, 2021, ICML.

Harmonizing Fully Optimal Designs with Classic Randomization in Fixed Trial Experiments.

A. Krieger, Uri Shalit, A. Kapelner, 2018, 1810.08389.

Scalable Sensitivity and Uncertainty Analysis for Causal-Effect Estimates of Continuous-Valued Interventions

N. Meinshausen, Y. Gal, Uri Shalit, 2022, ArXiv.

Reinforcement Learning with a Terminator

Assaf Hallak, Shie Mannor, Gal Dalal, 2022, ArXiv.

Tell me something interesting: Clinical utility of machine learning prediction models in the ICU

Uri Shalit, D. Eytan, Ofra Amir, 2022, J. Biomed. Informatics.

Scalable Sensitivity and Uncertainty Analysis for Causal-Effect Estimates of Continuous-Valued Interventions

N. Meinshausen, Y. Gal, Uri Shalit, 2022, NeurIPS.

During a Postural Task Mechanical Loads Applied to the Shoulder and Elbow Neural Activity in Primary Motor Cortex Related to

J. A. Pruszynski, R. Shadmehr, S. Scott, 2015 .

What drives performance in machine learning models for predicting heart failure outcome?

Uri Shalit, D. Aronson, O. Caspi, 2022, European heart journal. Digital health.

Malign Overfitting: Interpolation Can Provably Preclude Invariance

Y. Carmon, Uri Shalit, Gal Yona, 2022, ArXiv.

Harmonizing Optimized Designs With Classic Randomization in Experiments

Uri Shalit, Abba M. Krieger, Adam Kapelner, 2020 .

COVID-19 dynamics after a national immunization program in Israel

E. Segal, Uri Shalit, M. Gorfine, 2021, Nature Medicine.

Scalable streaming learning of dyadic relationships (שער נוסף בעברית: למידת יחסים דיאדיים ממידע זורם.)

Uri Shalit, Uri Shalit, 2015 .

FuncISH: learning a functional representation of neural ISH images

Gal Chechik, Uri Shalit, Noa Liscovitch, 2013, Bioinform..

Hospital load and increased COVID-19 related mortality in Israel

E. Segal, Uri Shalit, M. Gorfine, 2021, Nature Communications.

Development and validation of a machine learning model predicting illness trajectory and hospital utilization of COVID-19 patients: A nationwide study

Uri Shalit, M. Gorfine, D. Eytan, 2021, J. Am. Medical Informatics Assoc..

Socioeconomic disparities and COVID-19 vaccination acceptance: a nationwide ecologic study

Uri Shalit, G. Twig, O. Caspi, 2021, Clinical Microbiology and Infection.

Patterns of COVID-19 pandemic dynamics following deployment of a broad national immunization program

E. Segal, Uri Shalit, M. Gorfine, 2021, medRxiv.

Artificial Intelligence and Early Detection of Pancreatic Cancer

C. Sander, S. Brunak, L. Schwartz, 2021, Pancreas.

Artificial Intelligence and Early Detection of Pancreatic Cancer

C. Sander, S. Brunak, L. Schwartz, 2021, Pancreas.

An outbreak of equine botulism type D in Israel

Uri Shalit, A. Steinman, D. Elad, 2018 .

Efficient coordinate-descent for orthogonal matrices through Givens rotations pdf

Gal Chechik, Uri Shalit, Gal Chechik, 2013, ArXiv.

Explaining Classifiers with Causal Concept Effect (CaCE) pdf

Yash Goyal, Been Kim, Uri Shalit, 2019, ArXiv.

Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression

B. Schölkopf, B. Scholkopf, Uri Shalit, 2021, ICML.

Removing Hidden Confounding by Experimental Grounding

Uri Shalit, Aahlad Manas Puli, Nathan Kallus, 2018, NeurIPS.

Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression pdf

Krikamol Muandet, Uri Shalit, Bernhard Scholkopf, 2021, International Conference on Machine Learning.

Identifying Causal Effect Inference Failure with Uncertainty-Aware Models

Y. Gal, Uri Shalit, S. Mindermann, 2020, NeurIPS.

CausaLM: Causal Model Explanation Through Counterfactual Language Models

Uri Shalit, Roi Reichart, Amir Feder, 2020, CL.

On Calibration and Out-of-domain Generalization pdf

Uri Shalit, Amir Feder, Daniel Greenfeld, 2021, NeurIPS.

Generative ODE modeling with known unknowns

Uri Shalit, Danny Eytan, Ori Linial, 2020, CHIL.

Automated versus Do-It-Yourself Methods for Causal Inference: Lessons Learned from a Data Analysis Competition

Jennifer Hill, Uri Shalit, Marc Scott, 2017, Statistical Science.

Robust learning with the Hilbert-Schmidt independence criterion

Uri Shalit, Daniel Greenfeld, Uri Shalit, 2019, ICML.

Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data

Joost R. van Amersfoort, P. Tigas, Y. Gal, 2021, NeurIPS.

Using Deep Networks for Scientific Discovery in Physiological Signals

Uri Shalit, Danny Eytan, Tom Beer, 2020, MLHC.

Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects

Fredrik D. Johansson, D. Sontag, Uri Shalit, 2020, J. Mach. Learn. Res..

Off-Policy Evaluation in Partially Observable Environments

Shie Mannor, Uri Shalit, Guy Tennenholtz, 2019, AAAI.

B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding

Uri Shalit, Nathan Kallus, A. Jesson, 2023, 2304.10577.

Socioeconomic Disparities and COVID-19 Vaccination Acceptance: Experience from Israel

Uri Shalit, G. Twig, O. Caspi, 2021, medRxiv.

Corporate Social Responsibility via Multi-Armed Bandits

Omer Ben-Porat, Uri Shalit, Tom Ron, 2021, FAccT.

Online Learning in the Embedded Manifold of Low-rank Matrices

Daphna Weinshall, Gal Chechik, Uri Shalit, 2012, J. Mach. Learn. Res..

Can we learn individual-level treatment policies from clinical data?

Uri Shalit, Uri Shalit, 2019, Biostatistics.

Bandits with partially observable confounded data

Shie Mannor, Uri Shalit, Guy Tennenholtz, 2020, UAI.

Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects

Fredrik D. Johansson, D. Sontag, Uri Shalit, 2020, J. Mach. Learn. Res..

B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding

Uri Shalit, Nathan Kallus, A. Jesson, 2023, ICML.

On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning pdf

Shie Mannor, Gal Chechik, Uri Shalit, 2021, ICLR.

Evaluating the heterogeneous effect of extended incubation to blastocyst transfer on the implantation outcome via causal inference

Uri Shalit, M. Gavish, Yoav Kantor, 2021, bioRxiv.

Causal Effect Inference with Deep Latent-Variable Models

R. Zemel, J. Mooij, D. Sontag, 2017, ArXiv.

Supplementary Material Development and validation of a machine learning model predicting illness trajectory and hospital utilization of COVID-19 patients-a nationwide study

Uri Shalit, M. Gorfine, D. Eytan, 2020 .

Building Causal Graphs from Medical Literature and Electronic Medical Records

Kira Radinsky, Benny Kimelfeld, Uri Shalit, 2019, AAAI.

Bandits with Partially Observable Offline Data pdf

Shie Mannor, Uri Shalit, Guy Tennenholtz, 2020, ArXiv.

Causal Effect Inference with Deep Latent-Variable Models

R. Zemel, J. Mooij, D. Sontag, 2017, NIPS.

Commentary on “Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters”

Uri Shalit, 2022, INFORMS Journal on Data Science.

Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects

Fredrik D. Johansson, D. Sontag, Uri Shalit, 2020, J. Mach. Learn. Res..

Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds

Y. Carmon, Uri Shalit, G. Yona, 2023, ICLR.

Reinforcement Learning with a Terminator

Assaf Hallak, Shie Mannor, Gal Dalal, 2022, NeurIPS.