Predicting theNews of Tomorrow Using Patterns in Web Search Queries. - Kira Radinsky; Sagie Davidovich; Shaul Markovitch (Web Intelligence, 2008)

Ranking from pairs and triplets: information quality, evaluation methods and query complexity. - Kira Radinsky; Nir Ailon (WSDM, 2011)

A word at a time: computing word relatedness using temporal semantic analysis. - Kira Radinsky; Eugene Agichtein; Evgeniy Gabrilovich; Shaul Markovitch (WWW, 2011)

Time-sensitive query auto-completion. - Milad Shokouhi; Kira Radinsky (SIGIR, 2012)

Learning causality for news events prediction. - Kira Radinsky; Sagie Davidovich; Shaul Markovitch (WWW, 2012)

Modeling and predicting behavioral dynamics on the web. - Kira Radinsky; Krysta M. Svore; Susan T. Dumais; Jaime Teevan; Alex Bocharov; Eric Horvitz (WWW, 2012)

Learning to Predict from Textual Data. - Kira Radinsky; Sagie Davidovich; Shaul Markovitch (J. Artif. Intell. Res., 2012)

#TAIA2012. - Fernando Diaz 001; Susan T. Dumais; Kira Radinsky; Maarten de Rijke; Milad Shokouhi (SIGIR Forum, 2012)

Learning to Predict the Future using Web Knowledge and Dynamics. - Kira Radinsky (SIGIR Forum, 2012)

Learning to predict the future using Web knowledge and dynamics. - Kira Radinsky (2012)

SIGIR 2013 workshop on time aware information access (#TAIA2013). - Fernando Diaz 001; Susan T. Dumais; Miles Efron; Kira Radinsky; Maarten de Rijke; Milad Shokouhi (SIGIR, 2013)

Predicting content change on the web. - Kira Radinsky; Paul N. Bennett (WSDM, 2013)

Temporal web dynamics and its application to information retrieval. - Kira Radinsky; Fernando Diaz 001; Susan T. Dumais; Milad Shokouhi; Anlei Dong; Yi Chang 001 (WSDM, 2013)

Mining the web to predict future events. - Kira Radinsky; Eric Horvitz (WSDM, 2013)

Behavioral dynamics on the web: Learning, modeling, and prediction. - Kira Radinsky; Krysta M. Svore; Susan T. Dumais; Milad Shokouhi; Jaime Teevan; Alex Bocharov; Eric Horvitz (ACM Trans. Inf. Syst., 2013)

Named Entity Disambiguation for Noisy Text. - Yotam Eshel; Noam Cohen; Kira Radinsky; Shaul Markovitch; Ikuya Yamada; Omer Levy (CoNLL, 2017)

Learning Word Relatedness over Time. - Guy D. Rosin; Eytan Adar; Kira Radinsky (EMNLP, 2017)

Structuring the Unstructured: From Startup to Making Sense of eBay's Huge eCommerce Inventory. - Ido Guy; Kira Radinsky (SIGIR, 2017)

Latent Entities Extraction: How to Extract Entities that Do Not Appear in the Text? - Eylon Shoshan; Kira Radinsky (CoNLL, 2018)

Accelerating Prototype-Based Drug Discovery using Conditional Diversity Networks. - Shahar Harel; Kira Radinsky (KDD, 2018)

The BIG Web Track Chairs' Welcome & Organization. - Evgeniy Gabrilovich; Kira Radinsky; Kuansan Wang (WWW (Companion Volume), 2018)

Learning to Focus when Ranking Answers. - Dana Sagi; Tzoof Avny; Kira Radinsky; Eugene Agichtein (CoRR, 2018)

PGANs: Personalized Generative Adversarial Networks for ECG Synthesis to Improve Patient-Specific Deep ECG Classification. - Tomer Golany; Kira Radinsky (AAAI, 2019)

Separating Wheat from Chaff: Joining Biomedical Knowledge and Patient Data for Repurposing Medications. - Galia Nordon; Gideon Koren; Varda Shalev; Eric Horvitz; Kira Radinsky (AAAI, 2019)

Building Causal Graphs from Medical Literature and Electronic Medical Records. - Galia Nordon; Gideon Koren; Varda Shalev; Benny Kimelfeld; Uri Shalit; Kira Radinsky (AAAI, 2019)

Learning to Generate Personalized Product Descriptions. - Guy Elad; Ido Guy; Slava Novgorodov; Benny Kimelfeld; Kira Radinsky (CIKM, 2019)

Generating Timelines by Modeling Semantic Change. - Guy D. Rosin; Kira Radinsky (CoNLL, 2019)

Cross-Cultural Transfer Learning for Text Classification. - Dor Ringel; Gal Lavee; Ido Guy; Kira Radinsky (EMNLP/IJCNLP (1), 2019)

Node Embedding over Temporal Graphs. - Uriel Singer; Ido Guy; Kira Radinsky (IJCAI, 2019)

Explorations and Lessons Learned in Building an Autonomous Formula SAE Car from Simulations. - Dean Zadok; Tom Hirshberg; Amir Biran; Kira Radinsky; Ashish Kapoor (SIMULTECH, 2019)

Learning Novelty-Aware Ranking of Answers to Complex Questions. - Shahar Harel; Sefi Albo; Eugene Agichtein; Kira Radinsky (WWW, 2019)

Generating Product Descriptions from User Reviews. - Slava Novgorodov; Guy Elad; Ido Guy; Kira Radinsky (WWW, 2019)

Improving ECG Classification Using Generative Adversarial Networks. - Tomer Golany; Gal Lavee; Shai Tejman Yarden; Kira Radinsky (AAAI, 2020)

Chemical and Textual Embeddings for Drug Repurposing. - Galia Nordon; Levi Gottlieb; Kira Radinsky (AAAI, 2020)

tdGraphEmbed: Temporal Dynamic Graph-Level Embedding. - Moran Beladev; Lior Rokach; Gilad Katz; Ido Guy; Kira Radinsky (CIKM, 2020)

SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classification. - Tomer Golany; Kira Radinsky; Daniel Freedman (ICML, 2020)

Descriptions from the Customers: Comparative Analysis of Review-based Product Description Generation Methods. - Slava Novgorodov; Ido Guy; Guy Elad; Kira Radinsky (ACM Trans. Internet Techn., 2020)

ECG ODE-GAN: Learning Ordinary Differential Equations of ECG Dynamics via Generative Adversarial Learning. - Tomer Golany; Daniel Freedman; Kira Radinsky (AAAI, 2021)

Multi-Property Molecular Optimization using an Integrated Poly-Cycle Architecture. - Guy Barshatski; Galia Nordon; Kira Radinsky (CIKM, 2021)

12-Lead ECG Reconstruction via Koopman Operators. - Tomer Golany; Kira Radinsky; Daniel Freedman; Saar Minha (ICML, 2021)

Unpaired Generative Molecule-to-Molecule Translation for Lead Optimization. - Guy Barshatski; Kira Radinsky (KDD, 2021)

Event-Driven Query Expansion. - Guy D. Rosin; Ido Guy; Kira Radinsky (WSDM, 2021)

On biases of attention in scientific discovery. - Uriel Singer; Kira Radinsky; Eric Horvitz (Bioinform., 2021)

Learning to Rank Articles for Molecular Queries. - Galia Nordon; Aviram Magen; Ido Guy; Kira Radinsky (AAAI, 2022)

EqGNN: Equalized Node Opportunity in Graphs. - Uriel Singer; Kira Radinsky (AAAI, 2022)

Graph Neural Networks Pretraining Through Inherent Supervision for Molecular Property Prediction. - Roy Benjamin; Uriel Singer; Kira Radinsky (CIKM, 2022)

Temporal Attention for Language Models. - Guy D. Rosin; Kira Radinsky (NAACL-HLT (Findings), 2022)

Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly. - Dan Kalifa; Uriel Singer; Ido Guy; Guy D. Rosin; Kira Radinsky (WSDM, 2022)

Time Masking for Temporal Language Models. - Guy D. Rosin; Ido Guy; Kira Radinsky (WSDM, 2022)

What If: Generating Code to Answer Simulation Questions. - Gal Peretz; Kira Radinsky (CoRR, 2022)

tBDFS: Temporal Graph Neural Network Leveraging DFS. - Uriel Singer; Haggai Roitman; Ido Guy; Kira Radinsky (CoRR, 2022)

Gender-sensitive word embeddings for healthcare. - Shunit Agmon; Plia Gillis; Eric Horvitz; Kira Radinsky (J. Am. Medical Informatics Assoc., 2022)

Shielded Representations: Protecting Sensitive Attributes Through Iterative Gradient-Based Projection. - Shadi Iskander; Kira Radinsky; Yonatan Belinkov (ACL (Findings), 2023)

GraphERT- Transformers-based Temporal Dynamic Graph Embedding. - Moran Beladev; Gilad Katz; Lior Rokach; Uriel Singer; Kira Radinsky (CIKM, 2023)

CFOM: Lead Optimization For Drug Discovery With Limited Data. - Natan Kaminsky; Uriel Singer; Kira Radinsky (CIKM, 2023)

Generating Optimized Molecules without Patent Infringement. - Sally Turutov; Kira Radinsky (CIKM, 2023)

Clinical Contradiction Detection. - Dave Makhervaks; Plia Gillis; Kira Radinsky (EMNLP, 2023)

Self-supervised Classification of Clinical Multivariate Time Series using Time Series Dynamics. - Yakir Yehuda; Daniel Freedman; Kira Radinsky (KDD, 2023)

What If: Generating Code to Answer Simulation Questions in Chemistry Texts. - Gal Peretz; Mousa Arraf; Kira Radinsky (SIGIR, 2023)

Molecular Optimization Model with Patentability Constraint. - Sally Turutov; Kira Radinsky (AAAI, 2024)

Leveraging Prototypical Representations for Mitigating Social Bias without Demographic Information. - Shadi Iskander; Kira Radinsky; Yonatan Belinkov (NAACL (Short Papers), 2024)

CIQA: A Coding Inspired Question Answering Model. - Mousa Arraf; Kira Radinsky (SIGIR, 2024)

Interpretable Multivariate Time Series Forecasting Using Neural Fourier Transform. - Noam Koren; Kira Radinsky (CoRR, 2024)

GOProteinGNN: Leveraging Protein Knowledge Graphs for Protein Representation Learning. - Dan Kalifa; Uriel Singer; Kira Radinsky (CoRR, 2024)

Ordinary Differential Equations for Enhanced 12-Lead ECG Generation. - Yakir Yehuda; Kira Radinsky (CoRR, 2024)

Cross-Species Insights: Transforming Drug Efficacy from Rats to Humans Using Tissue-Specific Generative Models. - Sally Turutov; Kira Radinsky (KDD (1), 2025)

Predicting Oxidation Potentials with DFT-Driven Machine Learning. - Shweta Sharma; Natan Kaminsky; Kira Radinsky; Lilac Amirav (J. Chem. Inf. Model., 2025)

ReactEmbed: A Cross-Domain Framework for Protein-Molecule Representation Learning via Biochemical Reaction Networks. - Amitay Sicherman; Kira Radinsky (CoRR, 2025)

Docking-Aware Attention: Dynamic Protein Representations through Molecular Context Integration. - Amitay Sicherman; Kira Radinsky (CoRR, 2025)