Daniel Kifer

Professor of Computer Science & Engineering

Daniel Kifer

Most Recent Publications

Physics informed neural network can retrieve rate and state friction parameters from acoustic monitoring of laboratory stick-slip experiments

Prabhav Borate, Jacques Rivière, Samson Marty, Chris Marone, Daniel Kifer, Parisa Shokouhi, 2024, Scientific Reports

RECONSTRUCTION ATTACKS ON AGGRESSIVE RELAXATIONS OF DIFFERENTIAL PRIVACY

Prottay Protivash, John Durrell, Daniel Kifer, Zeyu Ding, Danfeng Zhang, 2024, Journal of Privacy and Confidentiality on p. 1-33

GEOGRAPHIC SPINES IN THE 2020 CENSUS DISCLOSURE AVOIDANCE SYSTEM

Ryan Cumings-Menon, Robert Ashmead, Daniel Kifer, Philip Leclerc, Jeffrey Ocker, Michael Ratcliffe, Pavel Zhuravlev, John M. Abowd, 2024, Journal of Privacy and Confidentiality

Reply to Muralidhar et al., Kenny et al., and Hotz et al.: The benefits of engagement with external research teams

Ron S. Jarmin, John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Nathan Goldschlag, Michael Hawes, Sallie Ann Keller, Daniel Kifer, Philip Leclerc, Jerome P. Reiter, Rolando A. Rodríguez, Ian Schmutte, Victoria A. Velkoff, Pavel I. Zhuravlev, 2024, Proceedings of the National Academy of Sciences of the United States of America

Investigating Symbolic Capabilities of Large Language Models

Neisarg Dave, Daniel Kifer, C. Lee Giles, Ankur Mali, 2024, CEUR Workshop Proceedings

EXACT PRIVACY ANALYSIS OF THE GAUSSIAN SPARSE HISTOGRAM MECHANISM

Brian Karrer, Daniel Kifer, Arjun Wilkins, Danfeng Zhang, 2024, Journal of Privacy and Confidentiality

PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise Binarization

Savinay Nagendra, Daniel Kifer, 2024, IEEE/CVF Winter Conference on Applications of Computer Vision on p. 1350-1361

Backpropagation-Free Deep Learning with Recursive Local Representation Alignment

Alexander G. Ororbia, Ankur Mali, Daniel Kifer, C. Lee Giles, 2023, on p. 9327-9335

An in-depth examination of requirements for disclosure risk assessment

Ron S. Jarmin, John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Nathan Goldschlag, Michael B. Hawes, Sallie Ann Keller, Daniel Kifer, Philip Leclerc, Jerome P. Reiter, Rolando A. Rodríguez, Ian Schmutte, Victoria A. Velkoff, Pavel Zhuravlev, 2023, Proceedings of the National Academy of Sciences of the United States of America

Using a physics-informed neural network and fault zone acoustic monitoring to predict lab earthquakes

Prabhav Borate, Jacques Rivière, Chris Marone, Ankur Mali, Daniel Kifer, Parisa Shokouhi, 2023, Nature Communications

Most-Cited Papers

Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network

Kuai Fang, Chaopeng Shen, Daniel Kifer, Xiao Yang, 2017, Geophysical Research Letters on p. 11,030-11,039

HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community

Chaopeng Shen, Eric Laloy, Amin Elshorbagy, Adrian Albert, Jerad Bales, Fi John Chang, Sangram Ganguly, Kuo Lin Hsu, Daniel Kifer, Zheng Fang, Kuai Fang, Dongfeng Li, Xiaodong Li, Wen Ping Tsai, 2018, Hydrology and Earth System Sciences on p. 5639-5656

Learning to extract semantic structure from documents using multimodal fully convolutional neural networks

Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer, Clyde Giles, 2017, on p. 4342–4351

Crime rate inference with big data

Hongjian Wang, Daniel Kifer, Corina Graif, Zhenhui Li, 2016, on p. 635-644

A Simple Baseline for Travel Time Estimation using Large-scale Trip Data

Hongjian Wang, Xianfeng Tang, Yu Hsuan Kuo, Daniel Kifer, Zhenhui Li, 2019, ACM Transactions on Intelligent Systems and Technology

Learning to read irregular text with attention mechanisms

Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles, 2017, on p. 3280-3286

A neural temporal model for human motion prediction

Anand Gopalakrishnan, Ankur Mali, Dan Kifer, Lee Giles, Alexander G. Ororbia, 2019, on p. 12108-12117

Concentrated differentially private gradient descent with adaptive per-iteration privacy budget

Jaewoo Lee, Daniel Kifer, 2018, on p. 1656-1665

Differentiable modelling to unify machine learning and physical models for geosciences

Chaopeng Shen, Alison P. Appling, Pierre Gentine, Toshiyuki Bandai, Hoshin Gupta, Alexandre Tartakovsky, Marco Baity-Jesi, Fabrizio Fenicia, Daniel Kifer, Li Li, Xiaofeng Liu, Wei Ren, Yi Zheng, Ciaran J. Harman, Martyn Clark, Matthew Farthing, Dapeng Fang, Dapeng Feng, Praveen Kumar, Doaa Aboelyazeed, Farshid Rahmani, Yalan Song, Hylke E. Beck, Tadd Bindas, Dipankar Dwivedi, Kuai Fang, Marvin Höge, Chris Rackauckas, Binayak Mohanty, Tirthankar Roy, Chonggang Xu, Kathryn Lawson, 2023, Nature Reviews Earth and Environment on p. 552-567

Multi-Scale Multi-Task FCN for Semantic Page Segmentation and Table Detection

Dafang He, Scott Cohen, Brian Price, Daniel Kifer, C. Lee Giles, 2017, on p. 254-261