selP: Selective tracking and presentation of data provenance. - Daniel Deutch; Amir Gilad; Yuval Moskovitch (ICDE, 2015)

Towards web-scale how-provenance. - Daniel Deutch; Amir Gilad; Yuval Moskovitch (ICDE Workshops, 2015)

Selective Provenance for Datalog Programs Using Top-K Queries. - Daniel Deutch; Amir Gilad; Yuval Moskovitch (Proc. VLDB Endow., 2015)

QPlain: Query by explanation. - Daniel Deutch; Amir Gilad (ICDE, 2016)

Learning Queries from Examples and Their Explanations. - Daniel Deutch; Amir Gilad (CoRR, 2016)

NLProv: Natural Language Provenance. - Daniel Deutch; Nave Frost; Amir Gilad (Proc. VLDB Endow., 2016)

Provenance for Natural Language Queries. - Daniel Deutch; Nave Frost; Amir Gilad (Proc. VLDB Endow., 2017)

Interactive Inference of SPARQL Queries Using Provenance. - Efrat Abramovitz; Daniel Deutch; Amir Gilad (ICDE, 2018)

Provenance for Non-Experts. - Daniel Deutch; Nave Frost; Amir Gilad (IEEE Data Eng. Bull., 2018)

QuestPro: Queries in SPARQL Through Provenance. - Efrat Abramovitz; Daniel Deutch; Amir Gilad (Proc. VLDB Endow., 2018)

NLProveNAns: Natural Language Provenance for Non-Answers. - Daniel Deutch; Nave Frost; Amir Gilad; Tomer Haimovich (Proc. VLDB Endow., 2018)

Natural Language Explanations for Query Results. - Daniel Deutch; Nave Frost; Amir Gilad (SIGMOD Rec., 2018)

Efficient provenance tracking for datalog using top-k queries. - Daniel Deutch; Amir Gilad; Yuval Moskovitch (VLDB J., 2018)

Reverse-Engineering Conjunctive Queries from Provenance Examples. - Daniel Deutch; Amir Gilad (EDBT, 2019)

Towards Inferring Queries from Simple and Partial Provenance Examples. - Amir Gilad; Yuval Moskovitch (CIKM, 2020)

Explaining Missing Query Results in Natural Language. - Daniel Deutch; Nave Frost; Amir Gilad; Tomer Haimovich (EDBT, 2020)

T-REx: Table Repair Explanations. - Daniel Deutch; Nave Frost; Amir Gilad; Oren Sheffer (SIGMOD Conference, 2020)

On Multiple Semantics for Declarative Database Repairs. - Amir Gilad; Daniel Deutch; Sudeepa Roy 001 (SIGMOD Conference, 2020)

ExplainED: Explanations for EDA Notebooks. - Daniel Deutch; Amir Gilad; Tova Milo; Amit Somech (Proc. VLDB Endow., 2020)

MuSe: Multiple Deletion Semantics for Data Repair. - Amir Gilad; Yihao Hu 001; Daniel Deutch; Sudeepa Roy 001 (Proc. VLDB Endow., 2020)

Explaining Natural Language query results. - Daniel Deutch; Nave Frost; Amir Gilad (VLDB J., 2020)

Data Provenance for Non-Experts - Amir Gilad (2020)

Explanations for Data Repair Through Shapley Values. - Daniel Deutch; Nave Frost; Amir Gilad; Oren Sheffer (CIKM, 2021)

PITA: Privacy Through Provenance Abstraction. - Daniel Deutch; Ariel Frankenthal; Amir Gilad; Yuval Moskovitch (ICDE, 2021)

On Optimizing the Trade-off between Privacy and Utility in Data Provenance. - Daniel Deutch; Ariel Frankenthal; Amir Gilad; Yuval Moskovitch (SIGMOD Conference, 2021)

Synthesizing Linked Data Under Cardinality and Integrity Constraints. - Amir Gilad; Shweta Patwa; Ashwin Machanavajjhala (SIGMOD Conference, 2021)

Detecting Treatment Effect Modifiers in Social Networks. - Amir Gilad; Harsh Parikh; Babak Salimi; Sudeepa Roy 001 (CoRR, 2021)

HypeR: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach. - Sainyam Galhotra; Amir Gilad; Sudeepa Roy 001; Babak Salimi (SIGMOD Conference, 2022)

Understanding Queries by Conditional Instances. - Amir Gilad; Zhengjie Miao; Sudeepa Roy 001; Jun Yang 001 (SIGMOD Conference, 2022)

FEDEX: An Explainability Framework for Data Exploration Steps. - Daniel Deutch; Amir Gilad; Tova Milo; Amit Mualem; Amit Somech (Proc. VLDB Endow., 2022)

DPXPlain: Privately Explaining Aggregate Query Answers. - Yuchao Tao; Amir Gilad; Ashwin Machanavajjhala; Sudeepa Roy 001 (Proc. VLDB Endow., 2022)

Causal What-If and How-To Analysis Using HypeR. - Fangzhu Shen; Kayvon Heravi; Oscar Gomez; Sainyam Galhotra; Amir Gilad; Sudeepa Roy 001; Babak Salimi (ICDE, 2023)

The Consistency of Probabilistic Databases with Independent Cells. - Amir Gilad; Aviram Imber; Benny Kimelfeld (ICDT, 2023)

Characterizing and Verifying Queries Via CINSGEN. - Hanze Meng; Zhengjie Miao; Amir Gilad; Sudeepa Roy 001; Jun Yang 001 (SIGMOD Conference Companion, 2023)

DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms. - Shweta Patwa; Danyu Sun; Amir Gilad; Ashwin Machanavajjhala; Sudeepa Roy 001 (Proc. VLDB Endow., 2023)

PreFair: Privately Generating Justifiably Fair Synthetic Data. - David Pujol; Amir Gilad; Ashwin Machanavajjhala (Proc. VLDB Endow., 2023)

Explaining Differentially Private Query Results With DPXPlain. - Tingyu Wang; Yuchao Tao; Amir Gilad; Ashwin Machanavajjhala; Sudeepa Roy 001 (Proc. VLDB Endow., 2023)

What Teaching Databases Taught Us about Researching Databases: Extended Talk Abstract. - Jun Yang 001; Amir Gilad; Yihao Hu 001; Hanze Meng; Zhengjie Miao; Sudeepa Roy 001; Kristin Stephens-Martinez (DataEd@SIGMOD, 2024)

How Database Theory Helps Teach Relational Queries in Database Education (Invited Talk). - Sudeepa Roy 001; Amir Gilad; Yihao Hu 001; Hanze Meng; Zhengjie Miao; Kristin Stephens-Martinez; Jun Yang 001 (ICDT, 2024)

First Workshop on Governance, Understanding and Integration of Data for Effective and Responsible AI (GUIDE-AI). - Abolfazl Asudeh; Sainyam Galhotra; Amir Gilad; Babak Salimi; Brit Youngmann (SIGMOD Conference Companion, 2024)

Summarized Causal Explanations For Aggregate Views (Full version). - Brit Youngmann; Michael J. Cafarella; Amir Gilad; Sudeepa Roy 001 (CoRR, 2024)

Qr-Hint: Actionable Hints Towards Correcting Wrong SQL Queries. - Yihao Hu 001; Amir Gilad; Kristin Stephens-Martinez; Sudeepa Roy 001; Jun Yang 001 (Proc. ACM Manag. Data, 2024)

Summarized Causal Explanations For Aggregate Views. - Brit Youngmann; Michael J. Cafarella; Amir Gilad; Sudeepa Roy 001 (Proc. ACM Manag. Data, 2024)

PD-Explain: A Unified Python-native Framework for Query Explanations Over DataFrames. - Itay Elyashiv; Amir Gilad; Edna Isakov; Tal Tikochinsky; Amit Somech (Proc. VLDB Endow., 2024)

Finding Convincing Views to Endorse a Claim. - Shunit Agmon; Amir Gilad; Brit Youngmann; Shahar Zoarets; Benny Kimelfeld (Proc. VLDB Endow., 2024)

The Cost of Representation by Subset Repairs. - Yuxi Liu; Fangzhu Shen; Kushagra Ghosh; Amir Gilad; Benny Kimelfeld; Sudeepa Roy 001 (Proc. VLDB Endow., 2024)

Demonstration of DPClustX: Differentially Private Explanations for Clusters. - Amir Gilad; Tova Milo; Kathy Razmadze; Ron Zadicario (SIGMOD Conference Companion, 2025)

CauSumX: Summarized Causal Explanations For Group-By-Average Queries. - Nativ Levy; Michael J. Cafarella; Amir Gilad; Sudeepa Roy 001; Brit Youngmann (SIGMOD Conference Companion, 2025)

Differentially private explanations for aggregate query answers. - Yuchao Tao; Amir Gilad; Ashwin Machanavajjhala; Sudeepa Roy 001 (VLDB J., 2025)

Refining Labeling Functions with Limited Labeled Data. - Chenjie Li; Amir Gilad; Boris Glavic; Zhengjie Miao; Sudeepa Roy 001 (CoRR, 2025)

Differentially Private Explanations for Clusters. - Amir Gilad; Tova Milo; Kathy Razmadze; Ron Zadicario (CoRR, 2025)

Computing Inconsistency Measures Under Differential Privacy. - Shubhankar Mohapatra; Amir Gilad; Xi He 001; Benny Kimelfeld (Proc. ACM Manag. Data, 2025)