Predicting Motivations of Actions by Leveraging Text. - Carl Vondrick; Deniz Oktay; Hamed Pirsiavash; Antonio Torralba 001 (CVPR, 2016)

Model Compression by Entropy Penalized Reparameterization. - Deniz Oktay; Johannes Ballé; Saurabh Singh; Abhinav Shrivastava (CoRR, 2019)

On Predictive Information Sub-optimality of RNNs. - Zhe Dong; Deniz Oktay; Ben Poole; Alexander A. Alemi (CoRR, 2019)

Scalable Model Compression by Entropy Penalized Reparameterization. - Deniz Oktay; Johannes Ballé; Saurabh Singh; Abhinav Shrivastava (ICLR, 2020)

Randomized Automatic Differentiation. - Deniz Oktay; Nick McGreivy; Joshua Aduol; Alex Beatson; Ryan P. Adams (ICLR, 2021)

Meta-PDE: Learning to Solve PDEs Quickly Without a Mesh. - Tian Qin; Alex Beatson; Deniz Oktay; Nick McGreivy; Ryan P. Adams (CoRR, 2022)

Neuromechanical Autoencoders: Learning to Couple Elastic and Neural Network Nonlinearity. - Deniz Oktay; Mehran Mirramezani; Eder Medina; Ryan P. Adams (ICLR, 2023)

JAX FDM: A differentiable solver for inverse form-finding. - Rafael Pastrana; Deniz Oktay; Ryan P. Adams; Sigrid Adriaenssens (CoRR, 2023)

Fiber Monte Carlo. - Nick Richardson; Deniz Oktay; Yaniv Ovadia; James C. Bowden; Ryan P. Adams (ICLR, 2024)

A rapid and automated computational approach to the design of multistable soft actuators. - Mehran Mirramezani; Deniz Oktay; Ryan P. Adams (Comput. Phys. Commun., 2024)

Graph Neural Networks Gone Hogwild. - Olga Solodova; Nick Richardson; Deniz Oktay; Ryan P. Adams (ICLR, 2025)