Search results

• 2024

  Bounding causal effects with leaky instruments

  Watson, D., Bravo-Hermsdorff, G., Gunderson, L. M., Penn, J., Mastouri, A. & Silva, R., Jul 2024, Proceedings of the 40th Conference on Uncertainty in Artificial Intelligence.

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

  • Causal Effect 100%
  • Variables 33%
  • Classical Approach 33%
  • Linear System 33%
  • Treatment Effect 33%

• Bounding Causal Effects with Leaky Instruments

  Watson, D. S., Penn, J., Gunderson, L. M., Bravo-Hermsdorff, G., Mastouri, A. & Silva, R., 2024, Proceedings of the 40th Conference on Uncertainty in Artificial Intelligence. Vol. 244. p. 3689-3710 22 p. (Proceedings of Machine Learning Research).

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

  • Causal Effect 100%
  • Classical Approach 33%
  • Linear System 33%
  • Treatment Effect 33%
  • Variable Method 33%
• 2023

  Adversarial Random Forests for Density Estimation and Generative Modeling

  Watson, D. S., Blesch, K., Kapar, J. & Wright, M. N., 2023, Proceedings of the 26th Conference on Artificial Intelligence and Statistics. Vol. 206. p. 5357-5375 19 p. (Proceedings of Machine Learning Research).

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

  Open Access

  • Random Decision Forest 100%
  • Density Estimation 100%
  • Superior Performance 50%
  • Data Generation 50%
  • Data Synthesis 50%
  11 Citations (Scopus)

• Explaining Predictive Uncertainty with Information Theoretic Shapley Values

  Watson, D. S., Tax, N., O'Hara, J., Mudd, R. & Guy, I., 1 Dec 2023, Advances in Neural Information Processing Systems. Vol. 36. (ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

  Open Access

  • Shapley Value 100%
  • Covariate Shift 100%
  • Covariate 33%
  • Information Theory 33%
  • Inference Procedure 33%
  7 Citations (Scopus)

• Intervention Generalization: A View from Factor Graph Models

  Bravo-Hermsdorff, G., Watson, D. S., Yu, J., Zeitler, J. & Silva, R., 2023, Advances in Neural Information Processing Systems. Vol. 36. p. 43662-43675 14 p. (ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

  • Factor Graph 100%
  • Training Data 100%
  • Causal Inference 100%
  • Coping Behavior 100%
  • Efficient Algorithm 50%
  1 Citation (Scopus)

• Intervention Generalization: A View from Factor Graph Models

  Bravo-Hermsdorff, G., Watson, D., Yu, J., Zeitler, J. & Silva, R., 1 Dec 2023, Advances in Neural Information Processing Systems. Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Curran Associates Inc., Vol. 36. p. 43662-43675 14 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

  Open Access

• Stochastic Causal Programming for Bounding Treatment Effects

  Padh, K., Zeitler, J., Watson, D., Kusner, M., Silva, R. & Kilbertus, N., 2023, Proceedings of The 2nd Conference on Causal Learning and Reasoning. Vol. 213. p. 142-176 35 p. (Proceedings of Machine Learning Research).

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

  Open Access

  • Treatment Effect 100%
  • Causal Effect 100%
  • Stochastics 100%
  • Monte Carlo 100%
  • Monte Carlo Method 100%
  7 Citations (Scopus)

• Unfooling SHAP and SAGE: Knockoff Imputation for Shapley Values

  Watson, D., 30 Oct 2023, World Conference on Explainable Artificial Intelligence.

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

  Open Access
• 2022

  Causal discovery under a confounder blanket

  Watson, D. & Silva, R., Aug 2022, Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence. Vol. 180. p. 2096-2106

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

  Open Access

  • Structure Learning 100%
  1 Citation (Scopus)

• Rational Shapley Values

  Watson, D., 21 Jun 2022, Proceedings of 2022 5th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2022. p. 1083-1094 12 p. (ACM International Conference Proceeding Series).

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

  Open Access

  File

  • Illustrates 100%
  • Constrains 100%
  • Complex Model 100%
  • Random Variable ξ 100%
  • Pragmatic Approach 100%
  13 Citations (Scopus)

  152 Downloads (Pure)
• 2021

  No explanation without inference

  Watson, D. S., 2021, AISB Convention 2021: Communication and Conversations. The Society for the Study of Artificial Intelligence and Simulation of Behaviour, (AISB Convention 2021: Communication and Conversations).

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

  Open Access

  • Concludes 100%
  • Linear Approximation 100%
  • Confounding 100%
  • Approximation Rule 100%
  • Scientific Explanation 100%

• Operationalizing complex causes: A pragmatic view of mediation

  Gultchin, L., Watson, D., Kusner, M. & Silva, R., Jul 2021, Proceedings of the 38th International Conference on Machine Learning. Vol. 139. p. 3875-3885

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

  Open Access

  • Two-Step Method 100%
  • Testing Procedure 100%
  • Gene Therapy 100%
  5 Citations (Scopus)
• 2020

  Causal feature learning for utility-maximizing agents

  Kinney, D. & Watson, D., Sept 2020, Proceedings of the 10th International Conference on Probabilistic Graphical Models. Vol. 138. p. 357-368

  Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

  Open Access

  • Representation Learning 100%
  • Learning Algorithm 28%
  • Theoretic Property 14%