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Deep Learning

1397 directly classified papers

Papers per year

Papers

Surveying the FAIRness of Annotation Tools: Difficult to find, difficult to reuse EACL 2024
SARAD: Spatial Association-Aware Anomaly Detection and Diagnosis for Multivariate Time Series NIPS 2024
Efficient LLM Scheduling by Learning to Rank NIPS 2024
Satformer: Accurate and Robust Traffic Data Estimation for Satellite Networks NIPS 2024
Neural Conditional Probability for Uncertainty Quantification NIPS 2024
DOFEN: Deep Oblivious Forest ENsemble NIPS 2024
Dynamic Neural Regeneration: Enhancing Deep Learning Generalization on Small Datasets NIPS 2024
DASH: Warm-Starting Neural Network Training in Stationary Settings without Loss of Plasticity NIPS 2024
Scaling transformer neural networks for skillful and reliable medium-range weather forecasting NIPS 2024
kubapok@LT-EDI 2024: Evaluating Transformer Models for Hate Speech Detection in Tamil EACL 2024
SEL-BALD: Deep Bayesian Active Learning with Selective Labels NIPS 2024
NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise NIPS 2024
Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox NIPS 2024
Neural Network Reparametrization for Accelerated Optimization in Molecular Simulations NIPS 2024
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines NIPS 2024
Interpretable Mesomorphic Networks for Tabular Data NIPS 2024
Structural Inference of Dynamical Systems with Conjoined State Space Models NIPS 2024
Explainable Depression Detection Using Large Language Models on Social Media Data EACL 2024
Frequency Adaptive Normalization For Non-stationary Time Series Forecasting NIPS 2024
A Layer-Wise Natural Gradient Optimizer for Training Deep Neural Networks NIPS 2024
Credal Deep Ensembles for Uncertainty Quantification NIPS 2024
Data-Driven Knowledge-Aware Inference of Private Information in Continuous Double Auctions AAAI 2024
AutoPSV: Automated Process-Supervised Verifier NIPS 2024
Advancing Spiking Neural Networks for Sequential Modeling with Central Pattern Generators NIPS 2024
Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks? NIPS 2024