A toolset of Python programs for signal modeling and indentification via sparse semilinear autoregressors.

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Deep LearningSPAAR
Overview
Owner
Fredy Vides
I am an applied operator theorist conducting research in operator approximation theory and its applications in mathematical modeling and numerical simulation.
Fredy Vides
Generative Modelling of BRDF Textures from Flash Images [SIGGRAPH Asia, 2021]

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Powerful unsupervised domain adaptation method for dense retrieval.

Powerful unsupervised domain adaptation method for dense retrieval

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COPA-SSE contains crowdsourced explanations for the Balanced COPA dataset

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BABEL: Bodies, Action and Behavior with English Labels [CVPR 2021]

BABEL is a large dataset with language labels describing the actions being performed in mocap sequences. BABEL labels about 43 hours of mocap sequences from AMASS [1] with action labels.

113 Dec 28, 2022
DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection

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AI grand challenge 2020 Repo (Speech Recognition Track)

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Companion code for "Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees"

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Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

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This repository contains code to run experiments in the paper "Signal Strength and Noise Drive Feature Preference in CNN Image Classifiers."

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A general 3D Object Detection codebase in PyTorch.

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FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

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CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation

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Orthogonal Over-Parameterized Training

The inductive bias of a neural network is largely determined by the architecture and the training algorithm. To achieve good generalization, how to effectively train a neural network is of great impo

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functorch is a prototype of JAX-like composable function transforms for PyTorch.

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A transformer-based method for Healthcare Image Captioning in Vietnamese

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MoViNets PyTorch implementation: Mobile Video Networks for Efficient Video Recognition;

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Denoising Diffusion Probabilistic Models

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