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07/27/2023
Speeding up Fourier Neural Operators via Mixed Precision
The Fourier neural operator (FNO) is a powerful technique for learning s...
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06/20/2023
InRank: Incremental Low-Rank Learning
The theory of greedy low-rank learning (GLRL) aims to explain the impres...
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06/15/2023
Fast Training of Diffusion Models with Masked Transformers
We propose an efficient approach to train large diffusion models with ma...
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05/25/2023
Voyager: An Open-Ended Embodied Agent with Large Language Models
We introduce Voyager, the first LLM-powered embodied lifelong learning a...
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03/04/2023
Prismer: A Vision-Language Model with An Ensemble of Experts
Recent vision-language models have shown impressive multi-modal generati...
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02/14/2023
Score-based Diffusion Models in Function Space
Diffusion models have recently emerged as a powerful framework for gener...
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02/12/2023
I^2SB: Image-to-Image Schrödinger Bridge
We propose Image-to-Image Schrödinger Bridge (I^2SB), a new class of con...
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11/28/2022
Incremental Fourier Neural Operator
Recently, neural networks have proven their impressive ability to solve ...
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11/24/2022
Fast Sampling of Diffusion Models via Operator Learning
Diffusion models have found widespread adoption in various areas. Howeve...
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10/23/2022
1st Place Solution of The Robust Vision Challenge (RVC) 2022 Semantic Segmentation Track
This report describes the winning solution to the semantic segmentation ...
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07/08/2022
Large Scale Mask Optimization Via Convolutional Fourier Neural Operator and Litho-Guided Self Training
Machine learning techniques have been extensively studied for mask optim...
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06/17/2022
MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge
Autonomous agents have made great strides in specialist domains like Ata...
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11/06/2021
Physics-Informed Neural Operator for Learning Partial Differential Equations
Machine learning methods have recently shown promise in solving partial ...
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10/25/2021
ZerO Initialization: Initializing Residual Networks with only Zeros and Ones
Deep neural networks are usually initialized with random weights, with a...
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09/08/2021
Panoptic SegFormer
We present Panoptic SegFormer, a general framework for end-to-end panopt...
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09/03/2021
U-FNO – an enhanced Fourier neural operator based-deep learning model for multiphase flow
Numerical simulation of multiphase flow in porous media is essential for...
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08/19/2021
Neural Operator: Learning Maps Between Function Spaces
The classical development of neural networks has primarily focused on le...
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07/05/2021
Long-Short Transformer: Efficient Transformers for Language and Vision
Transformers have achieved success in both language and vision domains. ...
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06/13/2021
Markov Neural Operators for Learning Chaotic Systems
Chaotic systems are notoriously challenging to predict because of their ...
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05/31/2021
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
We present SegFormer, a simple, efficient yet powerful semantic segmenta...
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10/18/2020
Fourier Neural Operator for Parametric Partial Differential Equations
The classical development of neural networks has primarily focused on le...
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07/23/2020
Explore More and Improve Regret in Linear Quadratic Regulators
Stabilizing the unknown dynamics of a control system and minimizing regr...
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11/05/2019
Memory Augmented Recursive Neural Networks
Recursive neural networks have shown an impressive performance for model...
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10/18/2018
Trust Region Policy Optimization of POMDPs
We propose Generalized Trust Region Policy Optimization (GTRPO), a Reinf...
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07/19/2017
