conftrace_

Architectures

27,448 papers (33 classified directly here)

Subtopics

Neural Networks (11,723) Transformers (10,397) Graph Neural Networks (4,522) Autoencoders (1,154) Convolutional Neural Networks (973) Recurrent Neural Networks (593) Generative Adversarial Networks (18) Encoder-Decoder (14)

Papers per year

27
213
2915
3174
'10
'15
'20
'25

Papers (including subtopics)

Beam Tree Recursive Cells ICML 2023
A New PHO-rmula for Improved Performance of Semi-Structured Networks ICML 2023
Constrained Monotonic Neural Networks ICML 2023
Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles ICML 2023
Provably and Practically Efficient Neural Contextual Bandits ICML 2023
Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective ICML 2023
TAN Without a Burn: Scaling Laws of DP-SGD ICML 2023
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure ICML 2023
Facial Expression Recognition with Adaptive Frame Rate based on Multiple Testing Correction ICML 2023
Modality-Agnostic Variational Compression of Implicit Neural Representations ICML 2023
Bigger, Better, Faster: Human-level Atari with human-level efficiency ICML 2023
Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning ICML 2023
Variational Autoencoding Neural Operators ICML 2023
Neural Markov Jump Processes ICML 2023
Multi-View Masked World Models for Visual Robotic Manipulation ICML 2023
Regularization-free Diffeomorphic Temporal Alignment Nets ICML 2023
Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods ICML 2023
UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers ICML 2023
Sequence Modeling with Multiresolution Convolutional Memory ICML 2023
Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space ICML 2023
Exphormer: Sparse Transformers for Graphs ICML 2023
Probabilistic Attention-to-Influence Neural Models for Event Sequences ICML 2023
Quantitative Universal Approximation Bounds for Deep Belief Networks ICML 2023
The Hessian perspective into the Nature of Convolutional Neural Networks ICML 2023
FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks ICML 2023