Danks, David

14 publications

ICLRW 2025 Do Vision-Language Models Have Internal World Models? Towards an Atomic Evaluation Qiyue Gao, Xinyu Pi, Kevin Liu, Junrong Chen, Ruolan Yang, Xinqi Huang, Xinyu Fang, Lu Sun, Gautham Kishore, Bo Ai, Stone Tao, Mengyang Liu, Jiaxi Yang, Chao-Jung Lai, Chuanyang Jin, Jiannan Xiang, Benhao Huang, David Danks, Hao Su, Tianmin Shu, Ziqiao Ma, Lianhui Qin, Zhiting Hu

NeurIPSW 2024 AI, Pluralism, and (Social) Compensation Nandhini Swaminathan, David Danks

CLeaR 2023 Causal Learning Through Deliberate Undersampling Kseniya Solovyeva, David Danks, Mohammadsajad Abavisani, Sergey Plis

ICLR 2023 GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints Mohammadsajad Abavisani, David Danks, Sergey Plis

NeurIPSW 2022 GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints Mohammadsajad Abavisani, David Danks, Vince Calhoun, Sergey Plis

NeurIPSW 2022 Reducing Causal Illusions Through Deliberate Undersampling Kseniya Solovyeva, David Danks, Mohammadsajad Abavisani, Sergey Plis

IJCAI 2017 Algorithmic Bias in Autonomous Systems David Danks, Alex John London

PGM 2016 Causal Discovery from Subsampled Time Series Data by Constraint Optimization Antti Hyttinen, Sergey Plis, Matti Järvisalo, Frederick Eberhardt, David Danks

UAI 2015 Mesochronal Structure Learning Sergey M. Plis, David Danks, Jianyu Yang

NeurIPS 2015 Rate-Agnostic (Causal) Structure Learning Sergey Plis, David Danks, Cynthia Freeman, Vince Calhoun

NeurIPS 2013 Tracking Time-Varying Graphical Structure Erich Kummerfeld, David Danks

NeurIPS 2008 Integrating Locally Learned Causal Structures with Overlapping Variables David Danks, Clark Glymour, Robert E. Tillman

NeurIPS 2002 Dynamical Causal Learning David Danks, Thomas L. Griffiths, Joshua B. Tenenbaum

UAI 2001 Linearity Properties of Bayes Nets with Binary Variables David Danks, Clark Glymour