{"list":"other","total":58,"rows":[{"id":"1412.6980","title":"Adam: A Method for Stochastic Optimization","created":"2014-12-22","cited_by_count":37240},{"id":"2002.05709","title":"A Simple Framework for Contrastive Learning of Visual Representations","created":"2020-02-13","cited_by_count":12049},{"id":"1609.02907","title":"Semi-Supervised Classification with Graph Convolutional Networks","created":"2016-09-09","cited_by_count":11361},{"id":"1807.03748","title":"Representation Learning with Contrastive Predictive Coding","created":"2018-07-10","cited_by_count":7777},{"id":"1911.05722","title":"Momentum Contrast for Unsupervised Visual Representation Learning","created":"2019-11-13","cited_by_count":7513},{"id":"1506.02142","title":"Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning","created":"2015-06-06","cited_by_count":4448},{"id":"1810.00826","title":"How Powerful are Graph Neural Networks?","created":"2018-10-01","cited_by_count":4393},{"id":"1612.01474","title":"Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles","created":"2016-12-05","cited_by_count":3926},{"id":"1901.00596","title":"A Comprehensive Survey on Graph Neural Networks","created":"2019-01-03","cited_by_count":2919},{"id":"2005.10242","title":"Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere","created":"2020-05-20","cited_by_count":1405},{"id":"1803.05407","title":"Averaging Weights Leads to Wider Optima and Better Generalization","created":"2018-03-14","cited_by_count":1209},{"id":"2010.13902","title":"Graph Contrastive Learning with Augmentations","created":"2020-10-22","cited_by_count":1208},{"id":"1809.10341","title":"Deep Graph Infomax","created":"2018-09-27","cited_by_count":1106},{"id":"1603.08861","title":"Revisiting Semi-Supervised Learning with Graph Embeddings","created":"2016-03-29","cited_by_count":976},{"id":"2006.05582","title":"Contrastive Multi-View Representation Learning on Graphs","created":"2020-06-10","cited_by_count":652},{"id":"2010.04592","title":"Contrastive Learning with Hard Negative Samples","created":"2020-10-09","cited_by_count":628},{"id":"1902.02476","title":"A Simple Baseline for Bayesian Uncertainty in Deep Learning","created":"2019-02-07","cited_by_count":560},{"id":"1505.05424","title":"Weight Uncertainty in Neural Networks","created":"2015-05-20","cited_by_count":554},{"id":"2006.04131","title":"Deep Graph Contrastive Representation Learning","created":"2020-06-07","cited_by_count":539},{"id":"1506.02557","title":"Variational Dropout and the Local Reparameterization Trick","created":"2015-06-08","cited_by_count":490},{"id":"2002.08791","title":"Bayesian Deep Learning and a Probabilistic Perspective of Generalization","created":"2020-02-20","cited_by_count":480},{"id":"2106.14806","title":"Laplace Redux -- Effortless Bayesian Deep Learning","created":"2021-06-28","cited_by_count":365},{"id":"2007.06823","title":"Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users","created":"2020-07-14","cited_by_count":338},{"id":"2104.14421","title":"What Are Bayesian Neural Network Posteriors Really Like?","created":"2021-04-29","cited_by_count":308},{"id":"2002.01169","title":"Graph Representation Learning via Graphical Mutual Information Maximization","created":"2020-02-04","cited_by_count":217},{"id":"2102.04803","title":"DetCo: Unsupervised Contrastive Learning for Object Detection","created":"2021-02-09","cited_by_count":205},{"id":"1906.02506","title":"Practical Deep Learning with Bayesian Principles","created":"2019-06-06","cited_by_count":158},{"id":"1806.04854","title":"Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam","created":"2018-06-13","cited_by_count":131},{"id":"2102.06571","title":"Bayesian Neural Network Priors Revisited","created":"2021-02-12","cited_by_count":121},{"id":"2109.01116","title":"An Empirical Study of Graph Contrastive Learning","created":"2021-09-02","cited_by_count":113},{"id":"2104.04975","title":"Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning","created":"2021-04-11","cited_by_count":106},{"id":"2106.11642","title":"Repulsive Deep Ensembles are Bayesian","created":"2021-06-22","cited_by_count":104},{"id":"2105.06868","title":"Priors in Bayesian Deep Learning: A Review","created":"2021-05-14","cited_by_count":101},{"id":"2007.05864","title":"Bayesian Deep Ensembles via the Neural Tangent Kernel","created":"2020-07-11","cited_by_count":90},{"id":"1906.01930","title":"Approximate Inference Turns Deep Networks into Gaussian Processes","created":"2019-06-05","cited_by_count":89},{"id":"2002.05551","title":"PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees","created":"2020-02-13","cited_by_count":85},{"id":"1603.04733","title":"Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors","created":"2016-03-15","cited_by_count":82},{"id":"2106.08320","title":"Self-Supervised Learning with Kernel Dependence Maximization","created":"2021-06-15","cited_by_count":77},{"id":"2003.03777","title":"Graphs, Convolutions, and Neural Networks: From Graph Filters to Graph Neural Networks","created":"2020-03-08","cited_by_count":75},{"id":"2110.02027","title":"ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning","created":"2021-10-05","cited_by_count":72},{"id":"2210.02330","title":"Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum","created":"2022-10-05","cited_by_count":43},{"id":"2202.10638","title":"Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations","created":"2022-02-22","cited_by_count":42},{"id":"1902.09754","title":"Function Space Particle Optimization for Bayesian Neural Networks","created":"2019-02-26","cited_by_count":41},{"id":"2210.00643","title":"Spectral Augmentation for Self-Supervised Learning on Graphs","created":"2022-10-02","cited_by_count":39},{"id":"2001.07620","title":"EdgeNets:Edge Varying Graph Neural Networks","created":"2020-01-21","cited_by_count":36},{"id":"2106.05586","title":"Data augmentation in Bayesian neural networks and the cold posterior effect","created":"2021-06-10","cited_by_count":36},{"id":"1912.05651","title":"Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection","created":"2019-12-11","cited_by_count":35},{"id":"2102.01691","title":"Exact Langevin Dynamics with Stochastic Gradients","created":"2021-02-02","cited_by_count":30},{"id":"2110.04403","title":"Temperature as Uncertainty in Contrastive Learning","created":"2021-10-08","cited_by_count":25},{"id":"2106.07512","title":"Last Layer Marginal Likelihood for Invariance Learning","created":"2021-06-14","cited_by_count":21},{"id":"2106.10760","title":"On Stein Variational Neural Network Ensembles","created":"2021-06-20","cited_by_count":21},{"id":"2105.06964","title":"BNNpriors: A library for Bayesian neural network inference with different prior distributions","created":"2021-05-14","cited_by_count":20},{"id":"2010.02038","title":"A Simple Framework for Uncertainty in Contrastive Learning","created":"2020-10-05","cited_by_count":16},{"id":"2202.12439","title":"Learning Invariant Weights in Neural Networks","created":"2022-02-25","cited_by_count":16},{"id":"2304.01762","title":"Incorporating Unlabelled Data into Bayesian Neural Networks","created":"2023-04-04","cited_by_count":9},{"id":"1909.07698","title":"Compositional uncertainty in deep Gaussian processes","created":"2019-09-17","cited_by_count":8},{"id":"2103.01730","title":"Graph-Time Convolutional Neural Networks","created":"2021-03-02","cited_by_count":8},{"id":"2112.07823","title":"Bayesian Graph Contrastive Learning","created":"2021-12-15","cited_by_count":3}],"next_cursor":null}