{"total":51,"rows":[{"id":"2103.16302","title":"Rethinking Spatial Dimensions of Vision Transformers","created":"2021-03-30","cited_by_count":361,"area":null},{"id":"2103.03024","title":"CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation","created":"2021-03-04","cited_by_count":227,"area":null},{"id":"2105.07926","title":"Towards Robust Vision Transformer","created":"2021-05-17","cited_by_count":137,"area":null},{"id":"2102.01063","title":"Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition","created":"2021-02-01","cited_by_count":73,"area":null},{"id":"2103.01315","title":"Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning","created":"2021-03-01","cited_by_count":56,"area":null},{"id":"2103.13558","title":"Efficient Feature Transformations for Discriminative and Generative Continual Learning","created":"2021-03-25","cited_by_count":50,"area":null},{"id":"2102.09972","title":"Implicit Regularization in Tensor Factorization","created":"2021-02-19","cited_by_count":44,"area":null},{"id":"2403.02241","title":"Neural Redshift: Random Networks are not Random Functions","created":"2024-03-04","cited_by_count":43,"area":null},{"id":"2103.01678","title":"Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance)","created":"2021-03-02","cited_by_count":35,"area":null},{"id":"2110.04541","title":"The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design","created":"2021-10-09","cited_by_count":33,"area":null},{"id":"2102.10032","title":"Approximation and Learning with Deep Convolutional Models: a Kernel Perspective","created":"2021-02-19","cited_by_count":31,"area":null},{"id":"2112.11325","title":"iSegFormer: Interactive Segmentation via Transformers with Application to 3D Knee MR Images","created":"2021-12-21","cited_by_count":28,"area":null},{"id":"2201.11729","title":"Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks","created":"2022-01-27","cited_by_count":27,"area":null},{"id":"2111.08308","title":"Learning with convolution and pooling operations in kernel methods","created":"2021-11-16","cited_by_count":21,"area":null},{"id":"2101.05186","title":"MC-LSTM: Mass-Conserving LSTM","created":"2021-01-13","cited_by_count":17,"area":null},{"id":"2205.02536","title":"YOLOPose: Transformer-based Multi-Object 6D Pose Estimation using Keypoint Regression","created":"2022-05-05","cited_by_count":17,"area":null},{"id":"2105.03928","title":"Which transformer architecture fits my data? A vocabulary bottleneck in self-attention","created":"2021-05-09","cited_by_count":16,"area":null},{"id":"2106.09259","title":"A Random CNN Sees Objects: One Inductive Bias of CNN and Its Applications","created":"2021-06-17","cited_by_count":15,"area":null},{"id":"2106.07148","title":"On the Sample Complexity of Learning under Invariance and Geometric Stability","created":"2021-06-14","cited_by_count":13,"area":null},{"id":"2503.10065","title":"Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild","created":"2025-03-13","cited_by_count":13,"area":null},{"id":"2506.04870","title":"Aligning Multimodal Representations through an Information Bottleneck","created":"2025-06-05","cited_by_count":13,"area":null},{"id":"2211.16494","title":"On the Ability of Graph Neural Networks to Model Interactions Between Vertices","created":"2022-11-29","cited_by_count":12,"area":null},{"id":"2305.09088","title":"The Hessian perspective into the Nature of Convolutional Neural Networks","created":"2023-05-16","cited_by_count":10,"area":null},{"id":"2112.03552","title":"Bootstrapping ViTs: Towards Liberating Vision Transformers from Pre-training","created":"2021-12-07","cited_by_count":8,"area":null},{"id":"2210.00223","title":"Contour-Aware Equipotential Learning for Semantic Segmentation","created":"2022-10-01","cited_by_count":6,"area":null},{"id":"2103.11785","title":"Entangled q-Convolutional Neural Nets","created":"2021-03-06","cited_by_count":4,"area":null},{"id":"2303.11249","title":"What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement","created":"2023-03-20","cited_by_count":4,"area":null},{"id":"2308.14418","title":"Multi-Scale and Multi-Layer Contrastive Learning for Domain Generalization","created":"2023-08-28","cited_by_count":4,"area":null},{"id":"2311.06224","title":"Harnessing Synthetic Datasets: The Role of Shape Bias in Deep Neural Network Generalization","created":"2023-11-10","cited_by_count":4,"area":null},{"id":"2212.12731","title":"Forecasting through deep learning and modal decomposition in two-phase concentric jets","created":"2022-12-24","cited_by_count":3,"area":null},{"id":"2307.11550","title":"YOLOPose V2: Understanding and Improving Transformer-based 6D Pose Estimation","created":"2023-07-21","cited_by_count":3,"area":null},{"id":"2310.07136","title":"Exponential Quantum Communication Advantage in Distributed Inference and Learning","created":"2023-10-11","cited_by_count":3,"area":null},{"id":"2406.05045","title":"A Tensor Decomposition Perspective on Second-order RNNs","created":"2024-06-07","cited_by_count":3,"area":null},{"id":"2209.09844","title":"Frequency Dropout: Feature-Level Regularization via Randomized Filtering","created":"2022-09-20","cited_by_count":2,"area":null},{"id":"2401.10373","title":"Harmonized Spatial and Spectral Learning for Robust and Generalized Medical Image Segmentation","created":"2024-01-18","cited_by_count":2,"area":null},{"id":"2104.01482","title":"Training Deep Normalizing Flow Models in Highly Incomplete Data Scenarios with Prior Regularization","created":"2021-04-03","cited_by_count":1,"area":null},{"id":"2301.00555","title":"Scene Structure Guidance Network: Unfolding Graph Partitioning into Pixel-Wise Feature Learning","created":"2023-01-02","cited_by_count":1,"area":null},{"id":"2401.03797","title":"Anatomy of Neural Language Models","created":"2024-01-08","cited_by_count":1,"area":null},{"id":"2408.13767","title":"Lecture Notes on Linear Neural Networks: A Tale of Optimization and Generalization in Deep Learning","created":"2024-08-25","cited_by_count":1,"area":null},{"id":"2411.10198","title":"STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing","created":"2024-11-15","cited_by_count":1,"area":null},{"id":"2603.24602","title":"MuViS: Multimodal Virtual Sensing Benchmark","created":"2026-03-13","cited_by_count":1,"area":null},{"id":"2103.06198","title":"Relational Weight Priors in Neural Networks for Abstract Pattern Learning and Language Modelling","created":"2021-03-10","cited_by_count":0,"area":null},{"id":"2109.03862","title":"Juvenile state hypothesis: What we can learn from lottery ticket hypothesis researches?","created":"2021-09-08","cited_by_count":0,"area":null},{"id":"2208.08191","title":"Transformer Vs. MLP-Mixer: Exponential Expressive Gap For NLP Problems","created":"2022-08-17","cited_by_count":0,"area":null},{"id":"2209.05777","title":"A lightweight Transformer-based model for fish landmark detection","created":"2022-09-13","cited_by_count":0,"area":null},{"id":"2305.17119","title":"Manifold Regularization for Memory-Efficient Training of Deep Neural Networks","created":"2023-05-26","cited_by_count":0,"area":null},{"id":"2312.08268","title":"Efficient Multi-Object Pose Estimation using Multi-Resolution Deformable Attention and Query Aggregation","created":"2023-12-13","cited_by_count":0,"area":null},{"id":"2601.09831","title":"A New Convergence Analysis of Plug-and-Play Proximal Gradient Descent Under Prior Mismatch","created":"2026-01-14","cited_by_count":0,"area":null},{"id":"2604.02201","title":"On the Role of Depth in the Expressivity of RNNs","created":"2026-04-02","cited_by_count":0,"area":null},{"id":"2605.24243","title":"GIBLy: Improving 3D Semantic Segmentation through an Architecture-Agnostic Lightweight Geometric Inductive Bias Layer","created":"2026-05-22","cited_by_count":0,"area":null},{"id":"2609.06546","title":"Introductory Notes on Learning$^2$","created":"2026-09-06","cited_by_count":0,"area":null}],"next_cursor":null}