Choi, Dami

9 publications

NeurIPS 2024 Connecting the Dots: LLMs Can Infer and Verbalize Latent Structure from Disparate Training Data Johannes Treutlein, Dami Choi, Jan Betley, Sam Marks, Cem Anil, Roger Grosse, Owain Evans

NeurIPS 2024 LLM Processes: Numerical Predictive Distributions Conditioned on Natural Language James Requeima, John Bronskill, Dami Choi, Richard E. Turner, David Duvenaud

ICMLW 2024 LLM Processes: Numerical Predictive Distributions Conditioned on Natural Language James Requeima, John F Bronskill, Dami Choi, Richard E. Turner, David Duvenaud

NeurIPS 2023 Order Matters in the Presence of Dataset Imbalance for Multilingual Learning Dami Choi, Derrick Xin, Hamid Dadkhahi, Justin Gilmer, Ankush Garg, Orhan Firat, Chih-Kuan Yeh, Andrew M Dai, Behrooz Ghorbani

NeurIPS 2023 Tools for Verifying Neural Models' Training Data Dami Choi, Yonadav Shavit, David K. Duvenaud

NeurIPS 2020 Gradient Estimation with Stochastic SoftMax Tricks Max Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J Maddison

NeurIPSW 2020 Self-Tuning Stochastic Optimization with Curvature-Aware Gradient Filtering Ricky T. Q. Chen, Dami Choi, Lukas Balles, David Duvenaud, Philipp Hennig

ICML 2019 Guided Evolutionary Strategies: Augmenting Random Search with Surrogate Gradients Niru Maheswaranathan, Luke Metz, George Tucker, Dami Choi, Jascha Sohl-Dickstein

ICLR 2018 Backpropagation Through the Void: Optimizing Control Variates for Black-Box Gradient Estimation Will Grathwohl, Dami Choi, Yuhuai Wu, Geoff Roeder, David Duvenaud