Neural Networks

The Analysis of Deep Neural Networks by Information Theory: From Explainability to Generalization AAAI 2023 The ART of Conversation: Measuring Phonetic Convergence and Deliberate Imitation in L2-Speech with a Siamese RNN Interspeech 2023 The Asymmetric Maximum Margin Bias of Quasi-Homogeneous Neural Networks ICLR 2023 The Best Defense Is a Good Offense: Adversarial Augmentation Against Adversarial Attacks CVPR 2023 The Catalog Problem: Clustering and Ordering Variable-Sized Sets ICML 2023 The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks NeurIPS 2023 The Contextual Lasso: Sparse Linear Models via Deep Neural Networks NeurIPS 2023 The CropAndWeed Dataset: A Multi-Modal Learning Approach for Efficient Crop and Weed Manipulation WACV 2023 The Dark Side of Dynamic Routing Neural Networks: Towards Efficiency Backdoor Injection CVPR 2023 The Devil is in the Upsampling: Architectural Decisions Made Simpler for Denoising with Deep Image Prior ICCV 2023 The DISPLACE Challenge 2023 - DIarization of SPeaker and LAnguage in Conversational Environments Interspeech 2023 The Hessian perspective into the Nature of Convolutional Neural Networks ICML 2023 The Implicit Bias of Batch Normalization in Linear Models and Two-layer Linear Convolutional Neural Networks COLT 2023 The Implicit Bias of Minima Stability in Multivariate Shallow ReLU Networks ICLR 2023 The Implicit Regularization of Momentum Gradient Descent in Overparametrized Models AAAI 2023 The Importance of Anti-Aliasing in Tiny Object Detection ACML 2023 The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks ICLR 2023 The Lie Derivative for Measuring Learned Equivariance ICLR 2023 The MALACH Corpus: Results with End-to-End Architectures and Pretraining Interspeech 2023 The Numerical Stability of Hyperbolic Representation Learning ICML 2023 Theoretical Analysis of the Inductive Biases in Deep Convolutional Networks NeurIPS 2023 Theoretical Conditions and Empirical Failure of Bracket Counting on Long Sequences with Linear Recurrent Networks EACL 2023 The Power of Recursion in Graph Neural Networks for Counting Substructures AISTATS 2023 The Simplicity Bias in Multi-Task RNNs: Shared Attractors, Reuse of Dynamics, and Geometric Representation NeurIPS 2023 The Surprising Effectiveness of Equivariant Models in Domains with Latent Symmetry ICLR 2023