Maheswaranathan, Niru

17 publications

CoLLAs 2022 Practical Tradeoffs Between Memory, Compute, and Performance in Learned Optimizers Luke Metz, C. Daniel Freeman, James Harrison, Niru Maheswaranathan, Jascha Sohl-dickstein

NeurIPS 2021 Reverse Engineering Learned Optimizers Reveals Known and Novel Mechanisms Niru Maheswaranathan, David Sussillo, Luke Metz, Ruoxi Sun, Jascha Sohl-Dickstein

ICLR 2021 The Geometry of Integration in Text Classification RNNs Kyle Aitken, Vinay Venkatesh Ramasesh, Ankush Garg, Yuan Cao, David Sussillo, Niru Maheswaranathan

NeurIPS 2021 Understanding How Encoder-Decoder Architectures Attend Kyle Aitken, Vinay Ramasesh, Yuan Cao, Niru Maheswaranathan

ICML 2020 How Recurrent Networks Implement Contextual Processing in Sentiment Analysis Niru Maheswaranathan, David Sussillo

NeurIPS 2019 From Deep Learning to Mechanistic Understanding in Neuroscience: The Structure of Retinal Prediction Hidenori Tanaka, Aran Nayebi, Niru Maheswaranathan, Lane McIntosh, Stephen Baccus, Surya Ganguli

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

ICMLW 2019 Line Attractor Dynamics in Recurrent Networks for Sentiment Classiﬁcation Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo

ICLR 2019 Meta-Learning Update Rules for Unsupervised Representation Learning Luke Metz, Niru Maheswaranathan, Brian Cheung, Jascha Sohl-Dickstein

NeurIPSW 2019 Revealing Computational Mechanisms of Retinal Prediction via Model Reduction Hidenori Tanaka, Aran Nayebi, Niru Maheswaranathan, Lane McIntosh, Stephen A. Baccus, Surya Ganguli

NeurIPS 2019 Reverse Engineering Recurrent Networks for Sentiment Classification Reveals Line Attractor Dynamics Niru Maheswaranathan, Alex Williams, Matthew Golub, Surya Ganguli, David Sussillo

ICML 2019 Understanding and Correcting Pathologies in the Training of Learned Optimizers Luke Metz, Niru Maheswaranathan, Jeremy Nixon, Daniel Freeman, Jascha Sohl-Dickstein

NeurIPS 2019 Universality and Individuality in Neural Dynamics Across Large Populations of Recurrent Networks Niru Maheswaranathan, Alex Williams, Matthew Golub, Surya Ganguli, David Sussillo

CVPRW 2018 Recurrent Segmentation for Variable Computational Budgets Lane McIntosh, Niru Maheswaranathan, David Sussillo, Jonathon Shlens

ICML 2017 Learned Optimizers That Scale and Generalize Olga Wichrowska, Niru Maheswaranathan, Matthew W. Hoffman, Sergio Gómez Colmenarejo, Misha Denil, Nando Freitas, Jascha Sohl-Dickstein

NeurIPS 2016 Deep Learning Models of the Retinal Response to Natural Scenes Lane McIntosh, Niru Maheswaranathan, Aran Nayebi, Surya Ganguli, Stephen Baccus

ICML 2015 Deep Unsupervised Learning Using Nonequilibrium Thermodynamics Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, Surya Ganguli