conftrace_

Architectures

30,950 papers (33 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Neural Networks (13,168) Transformers (11,186) Graph Neural Networks (5,491) Autoencoders (1,313) Convolutional Neural Networks (1,049) Recurrent Neural Networks (675) Generative Adversarial Networks (94) Encoder-Decoder (36)

Papers per year

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94

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536

912

1,611

2,559

3,004

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4,021

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1,439

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Papers (including subtopics)

WeatherGNN: Exploiting Meteo- and Spatial-Dependencies for Local Numerical Weather Prediction Bias-Correction IJCAI 2024 Weight Conditioning for Smooth Optimization of Neural Networks ECCV 2024 Weight decay induces low-rank attention layers NeurIPS 2024 Weighted Layer Averaging RoBERTa for Black-Box Machine-Generated Text Detection SemEval 2024 Weight-Sharing Regularization AISTATS 2024 Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes AAAI 2024 Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning NeurIPS 2024 Weisfeiler-Leman at the margin: When more expressivity matters ICML 2024 Weisfeiler Leman for Euclidean Equivariant Machine Learning ICML 2024 What Are You Token About? Differentiable Perturbed Top-k Token Selection for Scientific Document Summarization ACL 2024 What Can Transformer Learn with Varying Depth? Case Studies on Sequence Learning Tasks ICML 2024 What do Graph Neural Networks learn? Insights from Tropical Geometry NeurIPS 2024 What Do Hebbian Learners Learn? Reduction Axioms for Iterated Hebbian Learning AAAI 2024 What Do Transformers Know about Government? COLING 2024 What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding ICML 2024 What Is Missing For Graph Homophily? Disentangling Graph Homophily For Graph Neural Networks NeurIPS 2024 What is my quantum computer good for? Quantum capability learning with physics-aware neural networks NeurIPS 2024 What Languages are Easy to Language-Model? A Perspective from Learning Probabilistic Regular Languages ACL 2024 What Makes Language Models Good-enough? ACL 2024 What Matters in Graph Class Incremental Learning? An Information Preservation Perspective NeurIPS 2024 What Rotary Position Embedding Can Tell Us: Identifying Query and Key Weights Corresponding to Basic Syntactic or High-level Semantic Information NeurIPS 2024 What's in a Prior? Learned Proximal Networks for Inverse Problems ICLR 2024 What’s Mine becomes Yours: Defining, Annotating and Detecting Context-Dependent Paraphrases in News Interview Dialogs EMNLP 2024 When are dynamical systems learned from time series data statistically accurate? NeurIPS 2024 When can transformers reason with abstract symbols? ICLR 2024