autoencoders

All-atom Diffusion Transformers: Unified generative modelling of molecules and materials ICML 2025 Autoencoder-Based Hybrid Replay for Class-Incremental Learning ICML 2025 Distilling Structural Representations into Protein Sequence Models ICLR 2025 Epsilon-VAE: Denoising as Visual Decoding ICML 2025 EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling ICML 2025 Improving the Diffusability of Autoencoders ICML 2025 Learning View-invariant World Models for Visual Robotic Manipulation ICLR 2025 Masked Autoencoders Are Effective Tokenizers for Diffusion Models ICML 2025 Sparse Autoencoders, Again? ICML 2025 SUICA: Learning Super-high Dimensional Sparse Implicit Neural Representations for Spatial Transcriptomics ICML 2025 UniMoMo: Unified Generative Modeling of 3D Molecules for De Novo Binder Design ICML 2025 Universal Sparse Autoencoders: Interpretable Cross-Model Concept Alignment ICML 2025 Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models ICML 2024 Bootstrap AutoEncoders With Contrastive Paradigm for Self-supervised Gaze Estimation ICML 2024 Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth ICML 2024 Efficient World Models with Context-Aware Tokenization ICML 2024 Graph Geometry-Preserving Autoencoders ICML 2024 LaWa: Using Latent Space for In-Generation Image Watermarking ECCV 2024 Learned Rate Control for Frame-Level Adaptive Neural Video Compression via Dynamic Neural Network ECCV 2024 Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer ICML 2024 The Manifold Tangent Classifier NeurIPS 2011