{"list":"other","total":51,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1412.6980","title":"Adam: A Method for Stochastic Optimization","created":"2014-12-22","cited_by_count":37240},{"id":"2006.11239","title":"Denoising Diffusion Probabilistic Models","created":"2020-06-19","cited_by_count":21076},{"id":"1912.01703","title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","created":"2019-12-03","cited_by_count":20305},{"id":"1503.02531","title":"Distilling the Knowledge in a Neural Network","created":"2015-03-09","cited_by_count":10324},{"id":"1409.0575","title":"ImageNet Large Scale Visual Recognition Challenge","created":"2014-09-01","cited_by_count":8498},{"id":"1710.09412","title":"mixup: Beyond Empirical Risk Minimization","created":"2017-10-25","cited_by_count":5183},{"id":"1612.00796","title":"Overcoming catastrophic forgetting in neural networks","created":"2016-12-02","cited_by_count":4787},{"id":"2102.09672","title":"Improved Denoising Diffusion Probabilistic Models","created":"2021-02-18","cited_by_count":3761},{"id":"1912.04958","title":"Analyzing and Improving the Image Quality of StyleGAN","created":"2019-12-03","cited_by_count":3588},{"id":"1606.00915","title":"DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs","created":"2016-06-02","cited_by_count":3241},{"id":"1505.07818","title":"Domain-Adversarial Training of Neural Networks","created":"2015-05-28","cited_by_count":3044},{"id":"1710.10196","title":"Progressive Growing of GANs for Improved Quality, Stability, and Variation","created":"2017-10-27","cited_by_count":2988},{"id":"1607.00133","title":"Deep Learning with Differential Privacy","created":"2016-07-01","cited_by_count":2728},{"id":"1612.01105","title":"Pyramid Scene Parsing Network","created":"2016-12-04","cited_by_count":2479},{"id":"1802.07569","title":"Continual Lifelong Learning with Neural Networks: A Review","created":"2018-02-21","cited_by_count":1330},{"id":"1702.05464","title":"Adversarial Discriminative Domain Adaptation","created":"2017-02-17","cited_by_count":1311},{"id":"1705.08690","title":"Continual Learning with Deep Generative Replay","created":"2017-05-24","cited_by_count":1158},{"id":"1711.09601","title":"Memory Aware Synapses: Learning what (not) to forget","created":"2017-11-27","cited_by_count":1105},{"id":"1711.03213","title":"CyCADA: Cycle-Consistent Adversarial Domain Adaptation","created":"2017-11-08","cited_by_count":1082},{"id":"1908.03265","title":"On the Variance of the Adaptive Learning Rate and Beyond","created":"2019-08-08","cited_by_count":772},{"id":"2004.09666","title":"Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Images","created":"2020-04-20","cited_by_count":745},{"id":"2301.13188","title":"Extracting Training Data from Diffusion Models","created":"2023-01-30","cited_by_count":732},{"id":"1312.6211","title":"An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks","created":"2013-12-21","cited_by_count":722},{"id":"1801.04406","title":"Which Training Methods for GANs do actually Converge?","created":"2018-01-13","cited_by_count":679},{"id":"2106.00908","title":"TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification","created":"2021-06-02","cited_by_count":555},{"id":"1812.06499","title":"HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images","created":"2018-12-16","cited_by_count":388},{"id":"1812.02849","title":"A Survey of Unsupervised Deep Domain Adaptation","created":"2018-12-06","cited_by_count":361},{"id":"1710.10628","title":"Variational Continual Learning","created":"2017-10-29","cited_by_count":339},{"id":"1612.05424","title":"Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks","created":"2016-12-16","cited_by_count":308},{"id":"1802.05637","title":"cGANs with Projection Discriminator","created":"2018-02-15","cited_by_count":254},{"id":"2004.00440","title":"Semantic Drift Compensation for Class-Incremental Learning","created":"2020-04-01","cited_by_count":241},{"id":"2301.09515","title":"StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis","created":"2023-01-23","cited_by_count":212},{"id":"1904.03137","title":"Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning","created":"2019-04-05","cited_by_count":182},{"id":"1711.10563","title":"FearNet: Brain-Inspired Model for Incremental Learning","created":"2017-11-28","cited_by_count":177},{"id":"1901.05335","title":"A review of domain adaptation without target labels","created":"2019-01-16","cited_by_count":156},{"id":"2004.09199","title":"Generative Feature Replay For Class-Incremental Learning","created":"2020-04-20","cited_by_count":109},{"id":"2008.05571","title":"Self-Path: Self-supervision for Classification of Pathology Images with Limited Annotations","created":"2020-08-12","cited_by_count":89},{"id":"2006.07543","title":"GAN Memory with No Forgetting","created":"2020-06-13","cited_by_count":84},{"id":"1806.04498","title":"The Unusual Effectiveness of Averaging in GAN Training","created":"2018-06-12","cited_by_count":73},{"id":"2102.11057","title":"Hierarchical Graph Representations in Digital Pathology","created":"2021-02-22","cited_by_count":59},{"id":"1712.07436","title":"Incremental Adversarial Domain Adaptation for Continually Changing Environments","created":"2017-12-20","cited_by_count":52},{"id":"1904.06268","title":"ACE: Adapting to Changing Environments for Semantic Segmentation","created":"2019-04-12","cited_by_count":44},{"id":"2204.12454","title":"Differentiable Zooming for Multiple Instance Learning on Whole-Slide Images","created":"2022-04-26","cited_by_count":43},{"id":"2007.12942","title":"Gradient Regularized Contrastive Learning for Continual Domain Adaptation","created":"2020-07-25","cited_by_count":35},{"id":"1806.01357","title":"Adversarial Domain Adaptation for Classification of Prostate Histopathology Whole-Slide Images","created":"2018-06-04","cited_by_count":21},{"id":"2111.13353","title":"Contrastive Vicinal Space for Unsupervised Domain Adaptation","created":"2021-11-26","cited_by_count":14},{"id":"2301.02933","title":"Weakly Supervised Joint Whole-Slide Segmentation and Classification in Prostate Cancer","created":"2023-01-07","cited_by_count":10},{"id":"2108.09178","title":"Self-Rule to Multi-Adapt: Generalized Multi-source Feature Learning Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue Detection","created":"2021-08-20","cited_by_count":9},{"id":"2301.01211","title":"Generative appearance replay for continual unsupervised domain adaptation","created":"2023-01-03","cited_by_count":8},{"id":"2106.05350","title":"Generative Feature-driven Image Replay for Continual Learning","created":"2021-06-09","cited_by_count":3}],"next_cursor":null}