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Models

16,617 papers (23 classified directly here)

Subtopics

Generative Models (7,221) Diffusion Models (4,421) Large Language Models (2,733) Variational Inference (1,952) Language Models (732) Vision-Language Models (718) Foundation Models (278) Language Modeling (77) Sequence-to-Sequence (16) Variational Autoencoders (10) Neural Radiance Fields (9) Variational Autoencoder (8)

Papers per year

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62
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Papers (including subtopics)

The Generalized Reparameterization Gradient NIPS 2016
Neural Universal Discrete Denoiser NIPS 2016
Modelling Symbolic Music: Beyond the Piano Roll ACML 2016
Clamping Improves TRW and Mean Field Approximations AISTATS 2016
On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes AISTATS 2016
Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation AISTATS 2016
Relationship between PreTraining and Maximum Likelihood Estimation in Deep Boltzmann Machines AISTATS 2016
Variational Tempering AISTATS 2016
A Deep Generative Deconvolutional Image Model AISTATS 2016
A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016
Stochastic Neural Networks with Monotonic Activation Functions AISTATS 2016
Early Stopping as Nonparametric Variational Inference AISTATS 2016
Tight Variational Bounds via Random Projections and I-Projections AISTATS 2016
Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization AISTATS 2016
Weakly-supervised text-to-speech alignment confidence measure COLING 2016
Structured Generative Models of Continuous Features for Word Sense Induction COLING 2016
Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis CVPR 2016
MDL-CW: A Multimodal Deep Learning Framework With Cross Weights CVPR 2016
Deep Gaussian Conditional Random Field Network: A Model-Based Deep Network for Discriminative Denoising CVPR 2016
Accelerated Generative Models for 3D Point Cloud Data CVPR 2016
Longitudinal Face Modeling via Temporal Deep Restricted Boltzmann Machines CVPR 2016
Hierarchical Variational Models ICML 2016
A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models ICML 2016
Generative Adversarial Text to Image Synthesis ICML 2016
Deep Structured Energy Based Models for Anomaly Detection ICML 2016