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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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Papers (including subtopics)

Distribution Augmentation for Generative Modeling ICML 2020
Variational Autoencoders with Riemannian Brownian Motion Priors ICML 2020
On the Power of Compressed Sensing with Generative Models ICML 2020
Variational Inference for Sequential Data with Future Likelihood Estimates ICML 2020
Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities ICML 2020
On Implicit Regularization in $β$-VAEs ICML 2020
SGD Learns One-Layer Networks in WGANs ICML 2020
ACFlow: Flow Models for Arbitrary Conditional Likelihoods ICML 2020
Learning from Irregularly-Sampled Time Series: A Missing Data Perspective ICML 2020
InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs ICML 2020
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors ICML 2020
Hallucinative Topological Memory for Zero-Shot Visual Planning ICML 2020
Optimal transport mapping via input convex neural networks ICML 2020
Reliable Fidelity and Diversity Metrics for Generative Models ICML 2020
PolyGen: An Autoregressive Generative Model of 3D Meshes ICML 2020
Semi-Supervised StyleGAN for Disentanglement Learning ICML 2020
Non-Autoregressive Neural Text-to-Speech ICML 2020
Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks ICML 2020
DeepCoDA: personalized interpretability for compositional health data ICML 2020
Implicit Generative Modeling for Efficient Exploration ICML 2020
Normalizing Flows on Tori and Spheres ICML 2020
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models ICML 2020
Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures ICML 2020
Learning Robot Skills with Temporal Variational Inference ICML 2020
ControlVAE: Controllable Variational Autoencoder ICML 2020