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Deep Learning
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Neural Networks
11,300 papers
Papers per year
2002: 2
2003: 3
2006: 11
2007: 13
2008: 16
2009: 16
2010: 23
2011: 27
2012: 30
2013: 55
2014: 69
2015: 145
2016: 408
2017: 695
2018: 1065
2019: 1479
2020: 1348
2021: 1407
2022: 1147
2023: 1123
2024: 1083
2025: 811
2026: 324
Papers
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks
AAAI 2023
An Extreme-Adaptive Time Series Prediction Model Based on Probability-Enhanced LSTM Neural Networks
AAAI 2023
Safe Multi-View Deep Classification
AAAI 2023
MVCINN: Multi-View Diabetic Retinopathy Detection Using a Deep Cross-Interaction Neural Network
AAAI 2023
Recovering the Graph Underlying Networked Dynamical Systems under Partial Observability: A Deep Learning Approach
AAAI 2023
Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data
AAAI 2023
Boundary Graph Neural Networks for 3D Simulations
AAAI 2023
Why Capsule Neural Networks Do Not Scale: Challenging the Dynamic Parse-Tree Assumption
AAAI 2023
Fast Saturating Gate for Learning Long Time Scales with Recurrent Neural Networks
AAAI 2023
Backpropagation-Free Deep Learning with Recursive Local Representation Alignment
AAAI 2023
H-TSP: Hierarchically Solving the Large-Scale Traveling Salesman Problem
AAAI 2023
Dynamic Structure Pruning for Compressing CNNs
AAAI 2023
Experimental Observations of the Topology of Convolutional Neural Network Activations
AAAI 2023
Fixed-Weight Difference Target Propagation
AAAI 2023
Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling
AAAI 2023
Fast Convergence in Learning Two-Layer Neural Networks with Separable Data
AAAI 2023
DE-net: Dynamic Text-Guided Image Editing Adversarial Networks
AAAI 2023
Machines of Finite Depth: Towards a Formalization of Neural Networks
AAAI 2023
The Implicit Regularization of Momentum Gradient Descent in Overparametrized Models
AAAI 2023
AutoNF: Automated Architecture Optimization of Normalizing Flows with Unconstrained Continuous Relaxation Admitting Optimal Discrete Solution
AAAI 2023
Towards In-Distribution Compatible Out-of-Distribution Detection
AAAI 2023
Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting It into MLPs: An Effective GNN-to-MLP Distillation Framework
AAAI 2023
Decentralized Riemannian Algorithm for Nonconvex Minimax Problems
AAAI 2023
FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation
AAAI 2023
HALOC: Hardware-Aware Automatic Low-Rank Compression for Compact Neural Networks
AAAI 2023
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