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

2

3

15

13

18

17

27

39

43

74

94

221

536

912

1,611

2,559

3,004

3,504

3,729

4,021

4,550

4,519

1,439

'10

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Papers (including subtopics)

Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks ICLR 2024 Learning Plaintext-Ciphertext Cryptographic Problems via ANF-based SAT Instance Representation NeurIPS 2024 Learning Random Noise Salient Feature Fusion Siamese Network for Low-Resolution Object Tracking (Student Abstract) AAAI 2024 Learning Representations for Hierarchies with Minimal Support NeurIPS 2024 Learning rigid-body simulators over implicit shapes for large-scale scenes and vision NeurIPS 2024 Learning Saliency From Fixations WACV 2024 Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning ICLR 2024 Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling ICLR 2024 Learning Structure-Aware Representations of Dependent Types NeurIPS 2024 Learning Structure-from-Motion with Graph Attention Networks CVPR 2024 Learning sum of diverse features: computational hardness and efficient gradient-based training for ridge combinations COLT 2024 Learning Superconductivity from Ordered and Disordered Material Structures NeurIPS 2024 Learning symmetries via weight-sharing with doubly stochastic tensors NeurIPS 2024 Learning the greatest common divisor: explaining transformer predictions ICLR 2024 Learning to Act from Actionless Videos through Dense Correspondences ICLR 2024 Learning to Approximate Adaptive Kernel Convolution on Graphs AAAI 2024 Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching NeurIPS 2024 Learning to Compile Programs to Neural Networks ICML 2024 Learning to Compose: Improving Object Centric Learning by Injecting Compositionality ICLR 2024 Learning To Compose SuperWeights for Neural Parameter Allocation Search WACV 2024 Learning to compute Gröbner bases NeurIPS 2024 Learning to design protein-protein interactions with enhanced generalization ICLR 2024 Learning to Generate Rules for Realistic Few-Shot Relation Classification: An Encoder-Decoder Approach EMNLP 2024 Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks NeurIPS 2024 Learning to Merge Tokens via Decoupled Embedding for Efficient Vision Transformers NeurIPS 2024