Search Results for author: Renbo Tu

Found 8 papers, 5 papers with code

Guaranteed Approximation Bounds for Mixed-Precision Neural Operators

1 code implementation27 Jul 2023 Renbo Tu, Colin White, Jean Kossaifi, Boris Bonev, Nikola Kovachki, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar

Neural operators, such as Fourier Neural Operators (FNO), form a principled approach for learning solution operators for PDEs and other mappings between function spaces.

Operator learning

Self-supervised and Weakly Supervised Contrastive Learning for Frame-wise Action Representations

no code implementations6 Dec 2022 Minghao Chen, Renbo Tu, Chenxi Huang, Yuqi Lin, Boxi Wu, Deng Cai

In this paper, we introduce a new framework of contrastive action representation learning (CARL) to learn frame-wise action representation in a self-supervised or weakly-supervised manner, especially for long videos.

Action Classification Contrastive Learning +4

AutoML for Climate Change: A Call to Action

1 code implementation7 Oct 2022 Renbo Tu, Nicholas Roberts, Vishak Prasad, Sibasis Nayak, Paarth Jain, Frederic Sala, Ganesh Ramakrishnan, Ameet Talwalkar, Willie Neiswanger, Colin White

The challenge that climate change poses to humanity has spurred a rapidly developing field of artificial intelligence research focused on climate change applications.

AutoML

NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies

1 code implementation6 Oct 2022 Arjun Krishnakumar, Colin White, Arber Zela, Renbo Tu, Mahmoud Safari, Frank Hutter

Zero-cost proxies (ZC proxies) are a recent architecture performance prediction technique aiming to significantly speed up algorithms for neural architecture search (NAS).

Neural Architecture Search

Towards Deeper Generative Architectures for GANs using Dense connections

no code implementations30 Apr 2018 Samarth Tripathi, Renbo Tu

In this paper, we present the result of adopting skip connections and dense layers, previously used in image classification tasks, in the Fisher GAN implementation.

General Classification Image Classification

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