| 2026 | EDBT | Towards Guiding Data Imputation for Scientific Data Analytics Via SHAP-like Scores. | Omer Abramovich, Hadas Stiebel-Kalish, Daniel Deutch |
| 2026 | EDBT | CoDeC: Constraints-Guided Diverse Counterfactuals. | Avia Asael, Nave Frost, Amir Gilad, Daniel Deutch |
| 2024 | EDBT | Predicting Fact Contributions from Query Logs with Machine Learning. | Dana Arad, Daniel Deutch, Nave Frost |
| 2024 | EDBT | Optimizing Counterfactual-based Analysis of Machine Learning Models Through Databases. | Aviv Ben-Arie, Daniel Deutch, Nave Frost, Yair Horesh, Idan Meyuhas |
| 2024 | SP | CaFA: Cost-aware, Feasible Attacks With Database Constraints Against Neural Tabular Classifiers. | Matan Ben-Tov, Daniel Deutch, Nave Frost, Mahmood Sharif |
| 2023 | EMNLP | Answering Questions by Meta-Reasoning over Multiple Chains of Thought. | Ori Yoran, Tomer Wolfson, Ben Bogin, Uri Katz, Daniel Deutch, Jonathan Berant |
| 2022 | CIKM | LearnShapley: Learning to Predict Rankings of Facts Contribution Based on Query Logs. | Dana Arad, Daniel Deutch, Nave Frost |
| 2022 | CIKM | exML: An Explainable Maximum Likelihood Tool for Proportion Estimation in DNA Data. | Amit Bergman, Viviane Slon, Daniel Deutch |
| 2022 | NAACL | Weakly Supervised Text-to-SQL Parsing through Question Decomposition. | Tomer Wolfson, Daniel Deutch, Jonathan Berant |
| 2022 | SIGMOD | ShapGraph: An Holistic View of Explanations through Provenance Graphs and Shapley Values. | Susan B. Davidson, Daniel Deutch, Nave Frost, Benny Kimelfeld, Omer Koren, Mikal Monet |
| 2022 | SIGMOD | Computing the Shapley Value of Facts in Query Answering. | Daniel Deutch, Nave Frost, Benny Kimelfeld, Mikal Monet |
| 2022 | SIGMOD | Theory and Practice of Provenance. | Daniel Deutch, Tanu Malik, Adriane Chapman |
| 2022 | SIGMOD | CFDB: Machine Learning Model Analysis via Databases of CounterFactuals. | Idan Meyuhas, Aviv Ben-Arie, Yair Horesh, Daniel Deutch |
| 2021 | CIKM | Explanations for Data Repair Through Shapley Values. | Daniel Deutch, Nave Frost, Amir Gilad, Oren Sheffer |
| 2021 | ICDE | PITA: Privacy Through Provenance Abstraction. | Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch |
| 2021 | SIGMOD | On Optimizing the Trade-off between Privacy and Utility in Data Provenance. | Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch |
| 2020 | EDBT | Explaining Missing Query Results in Natural Language. | Daniel Deutch, Nave Frost, Amir Gilad, Tomer Haimovich |
| 2020 | SIGMOD | Equivalence-Invariant Algebraic Provenance for Hyperplane Update Queries. | Pierre Bourhis, Daniel Deutch, Yuval Moskovitch |
| 2020 | SIGMOD | T-REx: Table Repair Explanations. | Daniel Deutch, Nave Frost, Amir Gilad, Oren Sheffer |
| 2020 | SIGMOD | On Multiple Semantics for Declarative Database Repairs. | Amir Gilad, Daniel Deutch, Sudeepa Roy |
| 2019 | EDBT | Reverse-Engineering Conjunctive Queries from Provenance Examples. | Daniel Deutch, Amir Gilad |
| 2019 | ICDE | Explaining Queries Over Web Tables to Non-experts. | Jonathan Berant, Daniel Deutch, Amir Globerson, Tova Milo, Tomer Wolfson |
| 2019 | ICDE | Just in Time: Personal Temporal Insights for Altering Model Decisions. | Naama Boer, Daniel Deutch, Nave Frost, Tova Milo |
| 2019 | ICDE | Constraints-Based Explanations of Classifications. | Daniel Deutch, Nave Frost |
| 2019 | ICDE | COBRA: Compression Via Abstraction of Provenance for Hypothetical Reasoning. | Daniel Deutch, Yuval Moskovitch, Noam Rinetzky |
| 2019 | SIGMOD | Hypothetical Reasoning via Provenance Abstraction. | Daniel Deutch, Yuval Moskovitch, Noam Rinetzky |
| 2018 | CIKM | CEC: Constraints based Explanation for Classifications. | Daniel Deutch, Nave Frost |
| 2018 | CIKM | Preserving Privacy of Fraud Detection Rule Sharing Using Intel's SGX. | Daniel Deutch, Yehonatan Ginzberg, Tova Milo |
| 2018 | EDBT | Towards Hypothetical Reasoning Using Distributed Provenance. | Daniel Deutch, Yuval Moskovitch, Itay Polak, Noam Rinetzky |
| 2018 | ICDE | Interactive Inference of SPARQL Queries Using Provenance. | Efrat Abramovitz, Daniel Deutch, Amir Gilad |
| 2017 | CIDR | A Model for Fine-Grained Data Citation. | Susan B. Davidson, Daniel Deutch, Tova Milo, Gianmaria Silvello |
| 2017 | ICDE | POLYTICS: Provenance-Based Analytics of Data-Centric Applications. | Pierre Bourhis, Daniel Deutch, Yuval Moskovitch |
| 2017 | PODS | Data Citation: A Computational Challenge. | Susan B. Davidson, Peter Buneman, Daniel Deutch, Tova Milo, Gianmaria Silvello |
| 2017 | TIME | Possible and Certain Answers for Queries over Order-Incomplete Data. | Antoine Amarilli, Mouhamadou Lamine Ba, Daniel Deutch, Pierre Senellart |
| 2016 | EDBT | PROX: Approximated Summarization of Data Provenance. | Eleanor Ainy, Pierre Bourhis, Susan B. Davidson, Daniel Deutch, Tova Milo |
| 2016 | ICDE | Analyzing data-centric applications: Why, what-if, and how-to. | Pierre Bourhis, Daniel Deutch, Yuval Moskovitch |
| 2016 | ICDE | QPlain: Query by explanation. | Daniel Deutch, Amir Gilad |
| 2015 | CIKM | Approximated Summarization of Data Provenance. | Eleanor Ainy, Pierre Bourhis, Susan B. Davidson, Daniel Deutch, Tova Milo |
| 2015 | ICDE | selP: Selective tracking and presentation of data provenance. | Daniel Deutch, Amir Gilad, Yuval Moskovitch |
| 2015 | ICDE | Towards web-scale how-provenance. | Daniel Deutch, Amir Gilad, Yuval Moskovitch |
| 2014 | ICDT | Deduction with Contradictions in Datalog. | Serge Abiteboul, Daniel Deutch, Victor Vianu |
| 2014 | ICDT | Circuits for Datalog Provenance. | Daniel Deutch, Tova Milo, Sudeepa Roy, Val Tannen |
| 2013 | CIDR | Caravan: Provisioning for What-If Analysis. | Daniel Deutch, Zachary G. Ives, Tova Milo, Val Tannen |
| 2012 | ICDT | Finding optimal probabilistic generators for XML collections. | Serge Abiteboul, Yael Amsterdamer, Daniel Deutch, Tova Milo, Pierre Senellart |
| 2012 | WWW | Declarative platform for data sourcing games. | Daniel Deutch, Ohad Greenshpan, Boris Kostenko, Tova Milo |
| 2012 | SIGMOD | Mob data sourcing. | Daniel Deutch, Tova Milo |
| 2011 | ICDE | Using Markov Chain Monte Carlo to play Trivia. | Daniel Deutch, Ohad Greenshpan, Boris Kostenko, Tova Milo |
| 2011 | ICDT | Querying probabilistic business processes for sub-flows. | Daniel Deutch |
| 2011 | PODS | On provenance minimization. | Yael Amsterdamer, Daniel Deutch, Tova Milo, Val Tannen |
| 2011 | PODS | Provenance for aggregate queries. | Yael Amsterdamer, Daniel Deutch, Val Tannen |
| 2011 | PODS | A quest for beauty and wealth (or, business processes for database researchers). | Daniel Deutch, Tova Milo |
| 2010 | ICDE | Navigating through Mashed-up Applications with COMPASS. | Daniel Deutch, Ohad Greenshpan, Tova Milo |
| 2010 | PODS | On probabilistic fixpoint and Markov chain query languages. | Daniel Deutch, Christoph Koch, Tova Milo |
| 2009 | ICDE | Evaluating TOP-K Queries over Business Processes. | Daniel Deutch, Tova Milo |
| 2009 | ICDT | TOP-K projection queries for probabilistic business processes. | Daniel Deutch, Tova Milo |