Wide Residual Networks
Paper
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1605.07146
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Published
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2
Papers - ResNet
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Characterizing signal propagation to close the performance gap in unnormalized ResNets
Paper • 2101.08692 • Published • 2 -
Pareto-Optimal Quantized ResNet Is Mostly 4-bit
Paper • 2105.03536 • Published • 2 -
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations
Paper • 2106.01548 • Published • 2 -
ResNet strikes back: An improved training procedure in timm
Paper • 2110.00476 • Published • 3 -
A ResNet is All You Need? Modeling A Strong Baseline for Detecting Referable Diabetic Retinopathy in Fundus Images
Paper • 2210.03180 • Published -
Deep Residual Learning for Image Recognition
Paper • 1512.03385 • Published • 8 -
Revisiting ResNets: Improved Training and Scaling Strategies
Paper • 2103.07579 • Published • 2 -
Densely Connected Convolutional Networks
Paper • 1608.06993 • Published • 3 -
Aggregated Residual Transformations for Deep Neural Networks
Paper • 1611.05431 • Published • 2 -
RTSeg: Real-time Semantic Segmentation Comparative Study
Paper • 1803.02758 • Published • 2 -
Latent Diffusion Model for Medical Image Standardization and Enhancement
Paper • 2310.05237 • Published • 2 -
3D Medical Image Segmentation based on multi-scale MPU-Net
Paper • 2307.05799 • Published • 2 -
Joint Liver and Hepatic Lesion Segmentation in MRI using a Hybrid CNN with Transformer Layers
Paper • 2201.10981 • Published • 2 -
Bootstrap your own latent: A new approach to self-supervised Learning
Paper • 2006.07733 • Published • 2 -
From Modern CNNs to Vision Transformers: Assessing the Performance, Robustness, and Classification Strategies of Deep Learning Models in Histopathology
Paper • 2204.05044 • Published • 2 -
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology
Paper • 2203.00585 • Published • 2 -
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Paper • 1905.11946 • Published • 3 -
DAS: A Deformable Attention to Capture Salient Information in CNNs
Paper • 2311.12091 • Published • 2 -
Semi-Supervised Semantic Segmentation using Redesigned Self-Training for White Blood Cells
Paper • 2401.07278 • Published • 2 -
Adding Conditional Control to Text-to-Image Diffusion Models
Paper • 2302.05543 • Published • 57 -
Data Distributional Properties Drive Emergent In-Context Learning in Transformers
Paper • 2205.05055 • Published • 2 -
CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents
Paper • 2004.12629 • Published • 3 -
Realism in Action: Anomaly-Aware Diagnosis of Brain Tumors from Medical Images Using YOLOv8 and DeiT
Paper • 2401.03302 • Published • 1 -
Detecting and recognizing characters in Greek papyri with YOLOv8, DeiT and SimCLR
Paper • 2401.12513 • Published • 1 -
DeiT-LT Distillation Strikes Back for Vision Transformer Training on Long-Tailed Datasets
Paper • 2404.02900 • Published • 1 -
DeiT III: Revenge of the ViT
Paper • 2204.07118 • Published • 1 -
Transferable and Principled Efficiency for Open-Vocabulary Segmentation
Paper • 2404.07448 • Published • 12 -
ConsistencyDet: Robust Object Detector with Denoising Paradigm of Consistency Model
Paper • 2404.07773 • Published • 1 -
Long-form music generation with latent diffusion
Paper • 2404.10301 • Published • 27 -
GLIGEN: Open-Set Grounded Text-to-Image Generation
Paper • 2301.07093 • Published • 4 -
A Multimodal Automated Interpretability Agent
Paper • 2404.14394 • Published • 22 -
What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
Paper • 2404.07129 • Published • 3 -
Multiplication-Free Transformer Training via Piecewise Affine Operations
Paper • 2305.17190 • Published • 2 -
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Paper • 1809.11096 • Published • 1 -
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era
Paper • 1707.02968 • Published • 1 -
Emergence of Hidden Capabilities: Exploring Learning Dynamics in Concept Space
Paper • 2406.19370 • Published • 1 -
Poincaré ResNet
Paper • 2303.14027 • Published • 1 -
Equivariant Transformer Networks
Paper • 1901.11399 • Published • 1 -
Fixup Initialization: Residual Learning Without Normalization
Paper • 1901.09321 • Published • 1 -
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness
Paper • 2206.14502 • Published • 1 -
Geodesic Multi-Modal Mixup for Robust Fine-Tuning
Paper • 2203.03897 • Published • 1 -
RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer
Paper • 2407.17140 • Published • 2 -
DETRs Beat YOLOs on Real-time Object Detection
Paper • 2304.08069 • Published • 14 -
No More Adam: Learning Rate Scaling at Initialization is All You Need
Paper • 2412.11768 • Published • 43 -
Matryoshka Representation Learning
Paper • 2205.13147 • Published • 24