Generative Models

Learning to Explore for Stochastic Gradient MCMC ICML 2024 Learning To Generate Training Datasets for Robust Semantic Segmentation WACV 2024 Learning to Infer Generative Template Programs for Visual Concepts ICML 2024 Learning to Model the World With Language ICML 2024 Learning to Rank in Generative Retrieval AAAI 2024 Learning Transferable Features for Implicit Neural Representations NeurIPS 2024 Learning Visual Parkour from Generated Images CoRL 2024 Learning World Models for Unconstrained Goal Navigation NeurIPS 2024 LensNeRF: Rethinking Volume Rendering Based on Thin-Lens Camera Model WACV 2024 Let the Avatar Talk using Texts without Paired Training Data ECCV 2024 Leverage Class-Specific Accuracy to Guide Data Generation for Improving Image Classification ICML 2024 Leveraging Bitstream Metadata for Fast, Accurate, Generalized Compressed Video Quality Enhancement WACV 2024 Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data ICLR 2024 Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference ICML 2024 Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency ICLR 2024 LiFteR: Unleash Learned Codecs in Video Streaming with Loose Frame Referencing NSDI 2024 Lifting Architectural Constraints of Injective Flows ICLR 2024 Lighting Every Darkness with 3DGS: Fast Training and Real-Time Rendering for HDR View Synthesis NeurIPS 2024 Light Unbalanced Optimal Transport NeurIPS 2024 Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving Maps ICLR 2024 Linear-time Minimum Bayes Risk Decoding with Reference Aggregation ACL 2024 Linking in Style: Understanding learned features in deep learning models ECCV 2024 Liouville Flow Importance Sampler ICML 2024 Listenable Maps for Audio Classifiers ICML 2024 LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models NeurIPS 2024