generative model

Meta-DiffuB: A Contextualized Sequence-to-Sequence Text Diffusion Model with Meta-Exploration NeurIPS 2024 Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning WACV 2024 Metric Flow Matching for Smooth Interpolations on the Data Manifold NeurIPS 2024 MGF: Mixed Gaussian Flow for Diverse Trajectory Prediction NeurIPS 2024 Mind Artist: Creating Artistic Snapshots with Human Thought CVPR 2024 Minimax optimal density estimation using a shallow generative model with a one-dimensional latent variable AISTATS 2024 Mixed variational flows for discrete variables AISTATS 2024 ModaVerse: Efficiently Transforming Modalities with LLMs CVPR 2024 Model Collapse Demystified: The Case of Regression NeurIPS 2024 Modelling complex vector drawings with stroke-clouds ICLR 2024 Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference ICML 2024 Molecular Optimization Model with Patentability Constraint AAAI 2024 Molecule Design by Latent Prompt Transformer NeurIPS 2024 Molecule Generation with Fragment Retrieval Augmentation NeurIPS 2024 MorphVAE: Advancing Morphological Design of Voxel-Based Soft Robots with Variational Autoencoders AAAI 2024 Mosaic-SDF for 3D Generative Models CVPR 2024 Motion Diversification Networks CVPR 2024 MSA Generation with Seqs2Seqs Pretraining: Advancing Protein Structure Predictions NeurIPS 2024 Multimarginal Generative Modeling with Stochastic Interpolants ICLR 2024 Multimodal Large Language Models Make Text-to-Image Generative Models Align Better NeurIPS 2024 Multi-Step Denoising Scheduled Sampling: Towards Alleviating Exposure Bias for Diffusion Models AAAI 2024 Navigating Chemical Space with Latent Flows NeurIPS 2024 Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model NeurIPS 2024 Near-Optimal Distributionally Robust Reinforcement Learning with General L_p Norms NeurIPS 2024 Near-Optimality of Contrastive Divergence Algorithms NeurIPS 2024