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Probabilistic Modeling

2,599 papers

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Papers

Rethinking Variational Inference for Probabilistic Programs with Stochastic Support NIPS 2022
Logical Credal Networks NIPS 2022
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination NIPS 2022
Sparse Gaussian Process Hyperparameters: Optimize or Integrate? NIPS 2022
Inference and Sampling for Archimax Copulas NIPS 2022
Adjoint-aided inference of Gaussian process driven differential equations NIPS 2022
A Rotated Hyperbolic Wrapped Normal Distribution for Hierarchical Representation Learning NIPS 2022
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification NIPS 2022
Regularized Molecular Conformation Fields NIPS 2022
Efficient identification of informative features in simulation-based inference NIPS 2022
Bayesian Clustering of Neural Spiking Activity Using a Mixture of Dynamic Poisson Factor Analyzers NIPS 2022
Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance NIPS 2022
Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data NIPS 2022
Score-Based Diffusion meets Annealed Importance Sampling NIPS 2022
Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model NIPS 2022
Natural gradient enables fast sampling in spiking neural networks NIPS 2022
Probabilistic Missing Value Imputation for Mixed Categorical and Ordered Data NIPS 2022
Gaussian Copula Embeddings NIPS 2022
FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation NIPS 2022
Training Uncertainty-Aware Classifiers with Conformalized Deep Learning NIPS 2022
Kernel Interpolation with Sparse Grids NIPS 2022
Mesoscopic modeling of hidden spiking neurons NIPS 2022
Distinguishing discrete and continuous behavioral variability using warped autoregressive HMMs NIPS 2022
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits NIPS 2022
Discovery of Single Independent Latent Variable NIPS 2022