{"list":"other","total":63,"rows":[{"id":"1503.02531","title":"Distilling the Knowledge in a Neural Network","created":"2015-03-09","cited_by_count":10324},{"id":"1612.00796","title":"Overcoming catastrophic forgetting in neural networks","created":"2016-12-02","cited_by_count":4787},{"id":"2010.08895","title":"Fourier Neural Operator for Parametric Partial Differential Equations","created":"2020-10-18","cited_by_count":2908},{"id":"1606.09282","title":"Learning without Forgetting","created":"2016-06-29","cited_by_count":2496},{"id":"1610.02136","title":"A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks","created":"2016-10-07","cited_by_count":2385},{"id":"1611.07725","title":"iCaRL: Incremental Classifier and Representation Learning","created":"2016-11-23","cited_by_count":2333},{"id":"1910.03193","title":"DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators","created":"2019-10-08","cited_by_count":2018},{"id":"1706.08840","title":"Gradient Episodic Memory for Continual Learning","created":"2017-06-26","cited_by_count":1898},{"id":"2006.05525","title":"Knowledge Distillation: A Survey","created":"2020-06-09","cited_by_count":1603},{"id":"1807.03888","title":"A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks","created":"2018-07-10","cited_by_count":1485},{"id":"2012.07421","title":"WILDS: A Benchmark of in-the-Wild Distribution Shifts","created":"2020-12-14","cited_by_count":1375},{"id":"1606.04671","title":"Progressive Neural Networks","created":"2016-06-15","cited_by_count":1361},{"id":"1806.08734","title":"On the Spectral Bias of Neural Networks","created":"2018-06-22","cited_by_count":1341},{"id":"1706.02690","title":"Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks","created":"2017-06-08","cited_by_count":1328},{"id":"2010.03759","title":"Energy-based Out-of-distribution Detection","created":"2020-10-08","cited_by_count":1299},{"id":"1906.02530","title":"Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift","created":"2019-06-06","cited_by_count":1287},{"id":"1705.08690","title":"Continual Learning with Deep Generative Replay","created":"2017-05-24","cited_by_count":1158},{"id":"1811.11682","title":"Experience Replay for Continual Learning","created":"2018-11-28","cited_by_count":1095},{"id":"1812.00420","title":"Efficient Lifelong Learning with A-GEM","created":"2018-12-02","cited_by_count":1058},{"id":"1609.09106","title":"HyperNetworks","created":"2016-09-27","cited_by_count":1027},{"id":"1711.05769","title":"PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning","created":"2017-11-15","cited_by_count":898},{"id":"2302.00487","title":"A Comprehensive Survey of Continual Learning: Theory, Method and Application","created":"2023-01-31","cited_by_count":872},{"id":"2110.11334","title":"Generalized Out-of-Distribution Detection: A Survey","created":"2021-10-21","cited_by_count":802},{"id":"1801.10112","title":"Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence","created":"2018-01-30","cited_by_count":742},{"id":"1312.6211","title":"An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks","created":"2013-12-21","cited_by_count":722},{"id":"1801.01423","title":"Overcoming catastrophic forgetting with hard attention to the task","created":"2018-01-04","cited_by_count":681},{"id":"2308.08747","title":"An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning","created":"2023-08-17","cited_by_count":639},{"id":"1904.07734","title":"Three scenarios for continual learning","created":"2019-04-15","cited_by_count":614},{"id":"1908.04742","title":"Online Continual Learning with Maximally Interfered Retrieval","created":"2019-08-11","cited_by_count":379},{"id":"1611.06194","title":"Expert Gate: Lifelong Learning with a Network of Experts","created":"2016-11-18","cited_by_count":372},{"id":"1910.07104","title":"Orthogonal Gradient Descent for Continual Learning","created":"2019-10-15","cited_by_count":369},{"id":"2103.09762","title":"Gradient Projection Memory for Continual Learning","created":"2021-03-17","cited_by_count":348},{"id":"2106.14413","title":"Co$^2$L: Contrastive Continual Learning","created":"2021-06-28","cited_by_count":244},{"id":"2006.14769","title":"Supermasks in Superposition","created":"2020-06-26","cited_by_count":227},{"id":"2302.03648","title":"Class-Incremental Learning: A Survey","created":"2023-02-07","cited_by_count":209},{"id":"1910.14481","title":"Continual Unsupervised Representation Learning","created":"2019-10-31","cited_by_count":147},{"id":"1706.04859","title":"Sobolev Training for Neural Networks","created":"2017-06-15","cited_by_count":143},{"id":"2207.05748","title":"Physics-Informed Deep Neural Operator Networks","created":"2022-07-08","cited_by_count":113},{"id":"2010.11635","title":"Continual Learning in Low-rank Orthogonal Subspaces","created":"2020-10-22","cited_by_count":99},{"id":"2111.11210","title":"GCR: Gradient Coreset Based Replay Buffer Selection For Continual Learning","created":"2021-11-18","cited_by_count":95},{"id":"2110.12773","title":"Scientific Machine Learning Benchmarks","created":"2021-10-25","cited_by_count":60},{"id":"2007.12942","title":"Gradient Regularized Contrastive Learning for Continual Domain Adaptation","created":"2020-07-25","cited_by_count":35},{"id":"1908.00858","title":"Distilling Knowledge From a Deep Pose Regressor Network","created":"2019-08-02","cited_by_count":34},{"id":"2405.17583","title":"Understanding Forgetting in Continual Learning with Linear Regression","created":"2024-05-27","cited_by_count":30},{"id":"2108.06758","title":"An Investigation of Replay-based Approaches for Continual Learning","created":"2021-08-15","cited_by_count":26},{"id":"2402.02949","title":"Kernel PCA for Out-of-Distribution Detection","created":"2024-02-05","cited_by_count":24},{"id":"2105.04093","title":"Elastic Weight Consolidation (EWC): Nuts and Bolts","created":"2021-05-10","cited_by_count":23},{"id":"2101.00926","title":"CLeaR: An Adaptive Continual Learning Framework for Regression Tasks","created":"2021-01-04","cited_by_count":22},{"id":"2203.09450","title":"Continual Learning Based on OOD Detection and Task Masking","created":"2022-03-17","cited_by_count":21},{"id":"2505.22904","title":"Defining Foundation Models for Computational Science: A Call for Clarity and Rigor","created":"2025-05-28","cited_by_count":17},{"id":"2304.03894","title":"A multifidelity approach to continual learning for physical systems","created":"2023-04-08","cited_by_count":13},{"id":"2502.11756","title":"On the Computation of the Fisher Information in Continual Learning","created":"2025-02-17","cited_by_count":13},{"id":"2011.07801","title":"Gradient Episodic Memory with a Soft Constraint for Continual Learning","created":"2020-11-16","cited_by_count":12},{"id":"2206.14917","title":"Towards out of distribution generalization for problems in mechanics","created":"2022-06-29","cited_by_count":11},{"id":"2402.05379","title":"Trade-Offs of Diagonal Fisher Information Matrix Estimators","created":"2024-02-08","cited_by_count":10},{"id":"2307.04569","title":"Interpreting and generalizing deep learning in physics-based problems with functional linear models","created":"2023-07-10","cited_by_count":9},{"id":"2210.03869","title":"TAME: Task Agnostic Continual Learning using Multiple Experts","created":"2022-10-08","cited_by_count":8},{"id":"2508.21615","title":"Adapting to Change: A Comparison of Continual and Transfer Learning for Modeling Building Thermal Dynamics under Concept Drifts","created":"2025-08-29","cited_by_count":7},{"id":"2312.11973","title":"Continual Learning: Forget-free Winning Subnetworks for Video Representations","created":"2023-12-19","cited_by_count":6},{"id":"2410.06418","title":"MIRACLE3D: Memory-efficient Integrated Robust Approach for Continual Learning on Point Clouds via Shape Model Construction","created":"2024-10-08","cited_by_count":3},{"id":"2504.12503","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","created":"2025-04-16","cited_by_count":3},{"id":"2105.09241","title":"Gradient Methods with Memory","created":"2021-05-19","cited_by_count":1},{"id":"2305.16424","title":"SketchOGD: Memory-Efficient Continual Learning","created":"2023-05-25","cited_by_count":1}],"next_cursor":null}