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Data Augmentation Using Random Image Cropping and Patching for Deep CNNs

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Improved Techniques for Training Score-Based Generative Models

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BlockDrop: Dynamic Inference Paths in Residual Networks

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Dark Experience for General Continual Learning: a Strong, Simple Baseline

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Machine Learning with Membership Privacy using Adversarial Regularization

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Enforcing Analytic Constraints in Neural Networks Emulating Physical Systems

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Communication-Efficient Federated Learning for Wireless Edge Intelligence in IoT

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Transfer learning in hybrid classical-quantum neural networks

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XNOR-SRAM: In-Memory Computing SRAM Macro for Binary/Ternary Deep Neural Networks

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Prototype Augmentation and Self-Supervision for Incremental Learning

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Hierarchical Federated Learning ACROSS Heterogeneous Cellular Networks

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Training deep neural networks with low precision multiplications

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Robust fine-tuning of zero-shot models

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Attack of the tails: Yes, you really can backdoor federated learning

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With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations

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With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations

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Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations

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Prevalence of neural collapse during the terminal phase of deep learning training

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Deep Learning is Robust to Massive Label Noise

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Communication-efficient federated learning

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Test-Time Training with Self-Supervision for Generalization under Distribution Shifts

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Edge Intelligence: On-Demand Deep Learning Model Co-Inference with Device-Edge Synergy

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Learning to Quantize Deep Networks by Optimizing Quantization Intervals With Task Loss

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Learn To Pay Attention

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Few-Shot Incremental Learning with Continually Evolved Classifiers

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AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients

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Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks

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Exploring Simple Siamese Representation Learning

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Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention

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Class-Incremental Learning: A Survey

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Accelerating Federated Learning via Momentum Gradient Descent

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Variational Diffusion Models

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MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network

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Information dropout: learning optimal representations through noisy computation

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CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances

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Federated Deep Learning for Cyber Security in the Internet of Things: Concepts, Applications, and Experimental Analysis

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Deep Fuzzy Hashing Network for Efficient Image Retrieval

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Semantic Drift Compensation for Class-Incremental Learning

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Fractional Max-Pooling

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Generative Adversarial Networks in Time Series: A Systematic Literature Review

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Cross-Layer Distillation with Semantic Calibration

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Deep Structured Energy Based Models for Anomaly Detection

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Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses

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Regularized Evolution for Image Classifier Architecture Search

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Online Knowledge Distillation with Diverse Peers

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Interleaved Group Convolutions

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AutoFormer: Searching Transformers for Visual Recognition

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Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups

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Byzantine-Resilient Secure Federated Learning

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Expanding the Reach of Federated Learning by Reducing Client Resource Requirements

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Continuous learning in single-incremental-task scenarios

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GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models

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Local Binary Convolutional Neural Networks

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The relationship between trust in AI and trustworthy machine learning technologies

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Pervasive label errors in test sets destabilize machine learning benchmarks

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How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

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Visualizing the Hidden Activity of Artificial Neural Networks

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Federated learning in a medical context: A systematic literature review

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A Survey of Privacy Attacks in Machine Learning

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RobustBench: a standardized adversarial robustness benchmark

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Neural Photo Editing with Introspective Adversarial Networks

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Query-Efficient Hard-label Black-box Attack:An Optimization-based Approach

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Contrastive Learning with Stronger Augmentations

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Evaluating Differentially Private Machine Learning in Practice

Jayaraman, B., & Evans, D. (2019) · arXiv · doi:10.48550/arxiv.1902.08874 · Cited by 265

Tree-CNN: A hierarchical Deep Convolutional Neural Network for incremental learning

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Learning Filter Pruning Criteria for Deep Convolutional Neural Networks Acceleration

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Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning

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Defect Image Sample Generation With GAN for Improving Defect Recognition

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Testing machine learning based systems: a systematic mapping

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Februus: Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems

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A Survey on Semi-, Self- and Unsupervised Learning for Image Classification

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SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning

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Deep metric learning for few-shot image classification: A Review of recent developments

Li, X., Yang, X., Ma, Z., & Xue, J.-H. (2023) · Pattern Recognition · doi:10.1016/j.patcog.2023.109381 · Cited by 243

Effectively Unbiased FID and Inception Score and Where to Find Them

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Long Range Arena: A Benchmark for Efficient Transformers

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A Survey on Deep Hashing Methods

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FMA: A Dataset for Music Analysis

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Deep Learning for Generic Object Detection: A Survey

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Studying Very Low Resolution Recognition Using Deep Networks

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A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks

Belouadah, E., Popescu, A., & Kanellos, I. (2020) · arXiv · doi:10.48550/arxiv.2011.01844 · Cited by 235

Knowledge Distillation with the Reused Teacher Classifier

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Improving Neural Network Quantization without Retraining using Outlier Channel Splitting

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Delving into deep imbalanced regression

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Measuring the Effects of Data Parallelism on Neural Network Training

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Score-based Generative Modeling in Latent Space

Vahdat, A., Kreis, K., & Kautz, J. (2021) · arXiv · doi:10.48550/arxiv.2106.05931 · Cited by 224

A survey on few-shot class-incremental learning

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Benchmarking TinyML Systems: Challenges and Direction

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Multimodal Co-learning: Challenges, applications with datasets, recent advances and future directions

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Attention Guided Anomaly Localization in Images

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Overcoming catastrophic forgetting with hard attention to the task

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FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows

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Task-Oriented Communication for Multidevice Cooperative Edge Inference

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