2022

1. NeurIPS 2022

   STaR: Bootstrapping Reasoning With Reasoning

   Eric Zelikman*, Yuhuai (Tony) Wu*, Noah D. Goodman,

   NeurIPS 2022

2021

1. ICLR 2021

   Evaluating the Disentanglement of Deep Generative Models through Manifold Topology

   Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y Ng, Gunnar Carlsson, Stefano Ermon,

   International Conference on Learning Representations 2021

2020

1. ICML Workshop

   CRUDE: Calibrating Regression Uncertainty Distributions Empirically

   Eric Zelikman, Christopher Healy, Sharon Zhou, Anand Avati,

   ICML Workshop on Uncertainty & Robustness in Deep Learning 2020
2. NeurIPS Workshop

   Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models

   Eric Zelikman*, Sharon Zhou*, Jeremy Irvin*, Cooper Raterink, Hao Sheng, Jack Kelly, Ram Rajagopal, Andrew Y Ng, David Gagne,

   NeurIPS Workshop on Tackling Climate Change with Machine Learning 2020
3. CVPR Workshop

   Transferable Adversarial Attacks on Deep Reinforcement Learning

   Xinlei Pan, Yulong Cao, Xindi Wu, Eric Zelikman, Chaowei Xiao, Yanan Sui, Rudrasis Chakraborty, Ronald S. Fearing,

   Short Paper in CVPR Workshop on Adversarial Machine Learning in Computer Vision 2020
4. Honors Thesis

   Learning is its Own Reward: Exploring Worlds with Curiosity-driven Spiking Neural Networks

   Eric Zelikman (advised by Nick Haber),

   Undergraduate Honors Thesis 2020

2019

1. Learning as Reinforcement: Applying Principles of Neuroscience for More General Reinforcement Learning Agents

   Eric Zelikman, William Yin, Kenneth Wang,

   Non-refereed Poster at the California Cognitive Science Conference 2019

2018

1. Contextual Salience for Fast and Accurate Sentence Vectors

   Eric Zelikman, Richard Socher,

   arXiv 2018