Key papers

• QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networks (2026)
  Zhihan Zeng et al.
  4.39
• Multi-layer MIMO Relay as Deep Physical Neural Networks: Power Amplifiers as Activation Functions (2026)
  Meng Hua et al.
  4.39
• Convergence-Latency-Aware Adaptive Modulation and Resource Allocation in RIS-Assisted Wireless Federated Learning (2026)
  Liwei Wang et al.
  4.39
• Wavelet-based Variational Autoencoders for High-Resolution Image Generation (2025)
  Andrew Kiruluta
  2.76
• Variational Learning of Disentangled Representations (2025)
  Yuli Slavutsky et al.
  2.34
• Faithful Extreme Image Rescaling With Learnable Reversible Transformation And Semantic Priors (2026)
  Hao Wei, Yanhui Zhou, Chenyang Ge, et al.
  1.94
• Entropy-Based Characterisation of the Polarised Regime in Latent Variable Models (2026)
  Peter Clapham et al.
  1.89
• KL Divergence Between Gaussians: A Step-by-Step Derivation for the Variational Autoencoder Objective (2026)
  Andr\'es Mu\~noz and Rodrigo Ramele
  1.83
• CoVAE: correlated multimodal generative modeling (2026)
  Federico Caretti and Guido Sanguinetti
  1.78
• Manifold-Matching Autoencoders (2026)
  Laurent Cheret et al.
  1.78
• VQ-Style: Disentangling Style and Content in Motion with Residual Quantized Representations (2026)
  Fatemeh Zargarbashi et al.
  1.72
• Disentanglement by means of action-induced representations (2026)
  Gorka Mu\~noz-Gil et al.
  1.72
• EO-VAE: Towards A Multi-sensor Tokenizer for Earth Observation Data (2026)
  Nils Lehmann et al.
  1.72
• Hellinger Multimodal Variational Autoencoders (2026)
  Huyen Vo et al.
  1.67
• VENI: Variational Encoder for Natural Illumination (2026)
  Paul Walker and James A. D. Gardner and Andreea Ardelean and William A. P. Smith and Bernhard Egger
  1.67
• Iterative Amortized Hierarchical VAE (2026)
  Simon W. Penninga et al.
  1.67
• Learning Ordered Representations in Latent Space for Intrinsic Dimension Estimation via Principal Component Autoencoder (2026)
  Qipeng Zhan et al.
  1.67
• Training-Free Vector Quantization via Gaussian VAEs (2025)
  Tongda Xu et al.
  1.61
• Latent-Autoregressive GP-VAE Language Model (2025)
  Yves Ruffenach
  1.61
• Disentangled and Distilled Encoder for Out-of-Distribution Reasoning with Rademacher Guarantees (2025)
  Zahra Rahiminasab et al.
  1.61
• Variational Autoencoder for Calibration: A New Approach (2025)
  Travis Barrett et al.
  1.56
• Autoencoding Dynamics: Topological Limitations and Capabilities (2025)
  Matthew D. Kvalheim and Eduardo D. Sontag
  1.56
• Multivariate Variational Autoencoder (2025)
  Mehmet Can Yavuz
  1.56
• DeCo-VAE: Learning Compact Latents for Video Reconstruction via Decoupled Representation (2025)
  Xiangchen Yin et al.
  1.56
• Disentanglement of Sources in a Multi-Stream Variational Autoencoder (2025)
  Veranika Boukun and J\"org L\"ucke
  1.50
• Finding Manifolds With Bilinear Autoencoders (2025)
  Thomas Dooms et al.
  1.50
• Matricial Free Energy as a Gaussianizing Regularizer: Enhancing Autoencoders for Gaussian Code Generation (2025)
  Rishi Sonthalia and Raj Rao Nadakuditi
  1.50
• Latent Space Factorization in LoRA (2025)
  Shashi Kumar et al.
  1.50
• Distillation of a tractable model from the VQ-VAE (2025)
  Armin Had\v{z}i\'c et al.
  1.44
• Heavy-Tailed Class-Conditional Priors for Long-Tailed Generative Modeling (2025)
  Aymene Mohammed Bouayed and Samuel Deslauriers-Gauthier and Adrian Iaccovelli and David Naccache
  1.44
• Identifiable Autoregressive Variational Autoencoders for Nonlinear and Nonstationary Spatio-Temporal Blind Source Separation (2025)
  Mika Sipil\"a et al.
  1.44
• Ensemble Visualization With Variational Autoencoder (2025)
  Cenyang Wu et al.
  1.44
• Novel Phase-Noise-Tolerant Variational-Autoencoder-Based Equalization Suitable for Space-Division-Multiplexed Transmission (2025)
  Vincent Lauinger et al.
  1.44
• Multi-Scale Geometric Autoencoder (2025)
  Qipeng Zhan et al.
  1.44
• Discrete Variational Autoencoding via Policy Search (2025)
  Michael Drolet et al.
  1.44
• On the Shape of Latent Variables in a Denoising VAE-MoG: A Posterior Sampling-Based Study (2025)
  Fernanda Zapata Bascu\~n\'an
  1.44
• Negative Binomial Variational Autoencoders for Overdispersed Latent Modeling (2025)
  Yixuan Zhang et al.
  1.39
• Toward Architecture-Agnostic Local Control of Posterior Collapse in VAEs (2025)
  Hyunsoo Song et al.
  1.39
• Disentangled Deep Smoothed Bootstrap for Fair Imbalanced Regression (2025)
  Samuel Stocksieker et al.
  1.39
• HierCVAE: Hierarchical Attention-Driven Conditional Variational Autoencoders for Multi-Scale Temporal Modeling (2025)
  Yao Wu
  1.39
• Enhancing Interpretability in Generative Modeling: Statistically Disentangled Latent Spaces Guided by Generative Factors in Scientific Datasets (2025)
  Arkaprabha Ganguli et al.
  1.33
• L-VAE: Variational Auto-Encoder with Learnable Beta for Disentangled Representation (2025)
  Hazal Mogultay Ozcan et al.
  1.33
• Multi-Component VAE with Gaussian Markov Random Field (2025)
  Fouad Oubari et al.
  1.33
• From Points to Spheres: A Geometric Reinterpretation of Variational Autoencoders (2025)
  Songxuan Shi
  1.33
• Variational Adaptive Noise and Dropout towards Stable Recurrent Neural Networks (2025)
  Taisuke Kobayashi and Shingo Murata
  1.28
• Beyond Diagonal Covariance: Flexible Posterior VAEs via Free-Form Injective Flows (2025)
  Peter Sorrenson et al.
  1.28
• Variational Inference Optimized Using the Curved Geometry of Coupled Free Energy (2025)
  Kenric Nelson et al.
  1.28
• Approximately Equivariant Recurrent Generative Models for Quasi-Periodic Time Series with a Progressive Training Scheme (2025)
  Ruwen Fulek and Markus Lange-Hegermann
  1.22
• Variational Rank Reduction Autoencoders (2025)
  Jad Mounayer et al.
  1.22
• An Introduction to Discrete Variational Autoencoders (2025)
  Alan Jeffares et al.
  1.22
• Bidirectional Variational Autoencoders (2025)
  Bart Kosko et al.
  1.22
• Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling (2025)
  Xinxing Shi et al.
  1.22
• Information-theoretic Generalization Analysis for VQ-VAEs: A Role of Latent Variables (2025)
  Futoshi Futami et al.
  1.22
• Variational Self-Supervised Learning (2025)
  Mehmet Can Yavuz et al.
  1.17
• ACTIVA: Amortized Causal Effect Estimation via Transformer-based Variational Autoencoder (2025)
  Andreas Sauter and Saber Salehkaleybar and Aske Plaat and Erman Acar
  1.11
• Variational Autoencoder for Personalized Pathological Speech Enhancement (2025)
  Mingchi Hou and Ina Kodrasi
  1.11
• A Revisit of Total Correlation in Disentangled Variational Auto-Encoder with Partial Disentanglement (2025)
  Chengrui Li et al.
  1.06
• Multiple Invertible and Partial-Equivariant Function for Latent Vector Transformation to Enhance Disentanglement in VAEs (2025)
  Hee-Jun Jung et al.
  1.06
• Distributional Autoencoders Know the Score (2025)
  Andrej Leban
  1.06
• Enhanced uncertainty quantification variational autoencoders for the solution of Bayesian inverse problems (2025)
  Andrea Tonini et al.
  1.06