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Variational Inference

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TitleStatusHype
Decentralised Variational Inference Frameworks for Multi-object Tracking on Sensor Networks: Additional Notes—0
De-Confounded Variational Encoder-Decoder for Logical Table-to-Text Generation—0
Alpha-Beta Divergence For Variational Inference—0
Asynchronous Stochastic Variational Inference—0
Data-driven Seasonal Climate Predictions via Variational Inference and Transformers—0
All in the (Exponential) Family: Information Geometry and Thermodynamic Variational Inference—0
Celeste: Variational inference for a generative model of astronomical images—0
Accelerometer based Activity Classification with Variational Inference on Sticky HDP-SLDS—0
DDS2M: Self-Supervised Denoising Diffusion Spatio-Spectral Model for Hyperspectral Image Restoration—0
Decoupled Self-supervised Learning for Non-Homophilous Graphs—0
Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference—0
A deep adversarial approach based on multi-sensor fusion for remaining useful life prognostics—0
Cyclical Variational Bayes Monte Carlo for Efficient Multi-Modal Posterior Distributions Evaluation—0
A Stochastic approximation method for inference in probabilistic graphical models—0
Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations—0
Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework—0
Variational Conditional GAN for Fine-grained Controllable Image Generation—0
CRVI: Convex Relaxation for Variational Inference—0
Algorithms of the LDA model [REPORT]—0
CWAE-IRL: Formulating a supervised approach to Inverse Reinforcement Learning problem—0
Assessment of Uncertainty Quantification in Universal Differential Equations—0
B-SCST: Bayesian Self-Critical Sequence Training for Image Captioning—0
Bridging the inference gap in Mutimodal Variational Autoencoders—0
Addressing Cold-start Problem in Click-Through Rate Prediction via Supervised Diffusion Modeling—0
Cyberattack Detection using Deep Generative Models with Variational Inference—0
Data Association with Gaussian Processes—0
Decoupled Variational Gaussian Inference—0
Deep Probabilistic Programming—0
Algorithms for item categorization based on ordinal ranking data—0
Branching Stein Variational Gradient Descent for sampling multimodal distributions—0
Additive Multi-Index Gaussian process modeling, with application to multi-physics surrogate modeling of the quark-gluon plasma—0
Brain in the Dark: Design Principles for Neuro-mimetic Learning and Inference—0
A Survey on Brain-Inspired Deep Learning via Predictive Coding—0
A Sparsity-promoting Dictionary Model for Variational Autoencoders—0
Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty—0
C^2INet: Realizing Incremental Trajectory Prediction with Prior-Aware Continual Causal Intervention—0
A Statistically Principled and Computationally Efficient Approach to Speech Enhancement using Variational Autoencoders—0
Calibration of Model Uncertainty for Dropout Variational Inference—0
Correlated Random Measures—0
Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs—0
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data—0
A Sparse and Adaptive Prior for Time-Dependent Model Parameters—0
A Latent Variable Model for Two-Dimensional Canonical Correlation Analysis and its Variational Inference—0
CausalMMM: Learning Causal Structure for Marketing Mix Modeling—0
A Stochastic Decoder for Neural Machine Translation—0
Causal Semantic Communication for Digital Twins: A Generalizable Imitation Learning Approach—0
Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism—0
A Structured Variational Auto-encoder for Learning Deep Hierarchies of Sparse Features—0
Boosting Variational Inference With Locally Adaptive Step-Sizes—0
Boosting Variational Inference: an Optimization Perspective—0
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