conftrace_
← Topics

Deep Learning

66,648 papers (25 classified directly here)

Subtopics

Learning Types (28,663) Architectures (27,448) Models (16,617) Techniques (8,241) Optimization & Theory (6,829) Application Areas (46)

Papers per year

2
65
428
6150
10854
'05
'10
'15
'20
'25

Papers (including subtopics)

MPTSNet: Integrating Multiscale Periodic Local Patterns and Global Dependencies for Multivariate Time Series Classification AAAI 2025
Constrained Generative Modeling with Manually Bridged Diffusion Models AAAI 2025
GLAD: Improving Latent Graph Generative Modeling with Simple Quantization AAAI 2025
ALADE-SNN: Adaptive Logit Alignment in Dynamically Expandable Spiking Neural Networks for Class Incremental Learning AAAI 2025
Efficient Few-Shot Neural Architecture Search by Counting the Number of Nonlinear Functions AAAI 2025
Learning Deep Dissipative Dynamics AAAI 2025
Incomplete Multi-View Multi-Label Classification via Diffusion-Guided Redundancy Removal AAAI 2025
Deep Disentangled Metric Learning AAAI 2025
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors AAAI 2025
DHAKR: Learning Deep Hierarchical Attention-Based Kernelized Representations for Graph Classification AAAI 2025
Advancing Retrosynthesis with Retrieval-Augmented Graph Generation AAAI 2025
PEARL: Input-Agnostic Prompt Enhancement with Negative Feedback Regulation for Class-Incremental Learning AAAI 2025
Multimodal Variational Autoencoder: A Barycentric View AAAI 2025
PowerMLP: An Efficient Version of KAN AAAI 2025
Enhancing Masked Time-Series Modeling via Dropping Patches AAAI 2025
Efficient 3D Recognition with Event-driven Spike Sparse Convolution AAAI 2025
Slice-and-Pack: Tailoring Deep Models for Customized Requirements AAAI 2025
PrivDNFIS: Privacy-preserving and Efficient Deep Neuro-Fuzzy Inference System AAAI 2025
Monitoring Primitive Interactions During the Training of DNNs AAAI 2025
TTE: Two Tokens Are Enough to Improve Parameter-Efficient Tuning AAAI 2025
From PEFT to DEFT: Parameter Efficient Finetuning for Reducing Activation Density in Transformers AAAI 2025
FedPIA – Permuting and Integrating Adapters Leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning AAAI 2025
A Layer Selection Approach to Test Time Adaptation AAAI 2025
A Scalable and Effective Alternative to Graph Transformers AAAI 2025
RESQUE: Quantifying Estimator to Task and Distribution Shift for Sustainable Model Reusability AAAI 2025