Niru Maheswaranathan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
10
Venues
4
Active years
2015–2021
Best venue rank
A*
Where they publish
Papers
10 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2021 | ACSSC | A mechanistically interpretable model of the retinal neural code for natural scenes with multiscale adaptive dynamics. | Xuehao Ding, Dongsoo Lee, Satchel Grant, Heike Stein, Lane McIntosh, Niru Maheswaranathan, Stephen Baccus |
| 2021 | ICLR | The geometry of integration in text classification RNNs. | Kyle Aitken, Vinay Venkatesh Ramasesh, Ankush Garg, Yuan Cao, David Sussillo, Niru Maheswaranathan |
| 2020 | ICML | How recurrent networks implement contextual processing in sentiment analysis. | Niru Maheswaranathan, David Sussillo |
| 2019 | ICLR | Meta-Learning Update Rules for Unsupervised Representation Learning. | Luke Metz, Niru Maheswaranathan, Brian Cheung, Jascha Sohl-Dickstein |
| 2019 | ICML | Guided evolutionary strategies: augmenting random search with surrogate gradients. | Niru Maheswaranathan, Luke Metz, George Tucker, Dami Choi, Jascha Sohl-Dickstein |
| 2019 | ICML | Understanding and correcting pathologies in the training of learned optimizers. | Luke Metz, Niru Maheswaranathan, Jeremy Nixon, C. Daniel Freeman, Jascha Sohl-Dickstein |
| 2018 | CVPR | Recurrent Segmentation for Variable Computational Budgets. | Lane McIntosh, Niru Maheswaranathan, David Sussillo, Jonathon Shlens |
| 2018 | ICLR | Learning to Learn Without Labels. | Luke Metz, Niru Maheswaranathan, Brian Cheung, Jascha Sohl-Dickstein |
| 2017 | ICML | Learned Optimizers that Scale and Generalize. | Olga Wichrowska, Niru Maheswaranathan, Matthew W. Hoffman, Sergio Gomez Colmenarejo, Misha Denil, Nando de Freitas, Jascha Sohl-Dickstein |
| 2015 | ICML | Deep Unsupervised Learning using Nonequilibrium Thermodynamics. | Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, Surya Ganguli |