Dequantified Diffusion-Schrödinger Bridge for Density Ratio Estimation.

Neural Operator Variational Inference Based on Regularized Stein Discrepancy for Deep Gaussian Processes.

Fully Bayesian differential Gaussian processes through stochastic differential equations.

DeepAR-Attention probabilistic prediction for stock price series.

Neural Ordinary Differential Equation Networks for Fintech Applications Using Internet of Things.

Graph-Based Semantic Embedding Refinement for Zero-Shot Remote Sensing Image Scene Classification.

Generalized zero-shot action recognition through reservation-based gate and semantic-enhanced contrastive learning.

Consistent representation joint adaptive adjustment for incremental zero-shot learning.

Superclass-aware visual feature disentangling for generalized zero-shot learning.

Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling.

Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling.

Double Normalizing Flows: Flexible Bayesian Gaussian Process ODEs Learning.

Unbiased feature generating for generalized zero-shot learning.

Few-shot domain adaptation through compensation-guided progressive alignment and bias reduction.

Efficient Hardware for Generalized Turbo Signal Recovery in Compressed Sensing.

Low-Latency Segmented List-Pruning Software Polar List Decoder.

Low-Complexity Belief Propagation Detection for Correlated Large-Scale MIMO Systems.

Adaptive Preconditioned Iterative Linear Detection and Architecture for Massive MU-MIMO Uplink.