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github.com/mila-iqia/summerschool2015

mila-iqia/summerschool2015

Slides and exercises for the Deep Learning Summer School 2015 programming tutorials (⭐ 390)

github.com/huangyebiaoke/steel-pipe-weld-defect-detection

huangyebiaoke/steel-pipe-weld-defect-detection

Deep Learning Based Steel Pipe Weld Defect Detection (⭐ 103)

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arxiv.org/abs/2312.10105v5

SeiT++: Masked Token Modeling Improves Storage-efficient Training

Recent advancements in Deep Neural Network (DNN) models have significantly improved performance across computer vision tasks. However, achieving highly generalizable and high-performing vision models requires expansive datasets, resulting in signific...

arxiv.org/abs/2403.04114v1

Closing the Visual Sim-to-Real Gap with Object-Composable NeRFs

Deep learning methods for perception are the cornerstone of many robotic systems. Despite their potential for impressive performance, obtaining real-world training data is expensive, and can be impractically difficult for some tasks. Sim-to-real tran...

arxiv.org/abs/2007.10587v1

Learning to Compose Hypercolumns for Visual Correspondence

Feature representation plays a crucial role in visual correspondence, and recent methods for image matching resort to deeply stacked convolutional layers. These models, however, are both monolithic and static in the sense that they typically use a sp...

arxiv.org/abs/1304.3803v2

The Fate of Monsters in Anti-de Sitter Spacetime

Black hole entropy remains a deep puzzle: where does such enormous amount of entropy come from? Curiously, there exist gravitational configurations that possess even larger entropy than a black hole of the same mass, in fact, arbitrarily high entropy...

arxiv.org/abs/2210.15392v2

LeNo: Adversarial Robust Salient Object Detection Networks with Learnable Noise

Pixel-wise prediction with deep neural network has become an effective paradigm for salient object detection (SOD) and achieved remarkable performance. However, very few SOD models are robust against adversarial attacks which are visually imperceptib...

github.com/dougbrion/pytorch-classification-uncertainty

dougbrion/pytorch-classification-uncertainty

This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty" (⭐ 513)

github.com/yaringal/DropoutUncertaintyExps

yaringal/DropoutUncertaintyExps

Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning" (⭐ 581)

www.reddit.com/r/books/comments/1ovv8qx/the_city_and_its_uncertain_walls/

The city and its uncertain walls

Just finished this book by Murakami at first, I thought it wasn’t worth reading for the first few chapters, but as I went deeper into it, I found myself kneeling down and begging for forgiveness for...

github.com/HuiZeng/BIQA_Toolbox

HuiZeng/BIQA_Toolbox

A benchmark implementation of representative deep BIQA models (⭐ 118)

github.com/garyhost2/kidney-ultrasound-renal-failure-detection

garyhost2/kidney-ultrasound-renal-failure-detection

**RenalNet** is an end-to-end machine learning solution designed to predict renal failure from ultrasound images. This project leverages advanced deep learning techniques, custom data augmentation, and robust training strategies to build a clinical diagnostic…

arxiv.org/abs/2601.07821v1

Failure-Aware RL: Reliable Offline-to-Online Reinforcement Learning with Self-Re…

Post-training algorithms based on deep reinforcement learning can push the limits of robotic models for specific objectives, such as generalizability, accuracy, and robustness. However, Intervention-requiring Failures (IR Failures) (e.g., a robot spi...

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GitHub - google-deepmind/alphaevolve_results

Specifically, the repository contains a Google Colab notebook with the mathematical discoveries of AlphaEvolve outlined in Section 3 of the paper, as well as the corresponding code for verifying their …

github.com/amanjeetsahu/Natural-Language-Processing-Specialization

amanjeetsahu/Natural-Language-Processing-Specialization

This repo contains my coursework, assignments, and Slides for Natural Language Processing Specialization by deeplearning.ai on Coursera (⭐ 856)

github.com/greyhatguy007/Machine-Learning-Specialization-Coursera

greyhatguy007/Machine-Learning-Specialization-Coursera

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG (⭐ 7058)

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