Saved in:
| Main Authors: | Ichikawa, Yuma, Hukushima, Koji |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2309.07663 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Statistical Mechanics of Min-Max Problems
by: Ichikawa, Yuma, et al.
Published: (2024)
by: Ichikawa, Yuma, et al.
Published: (2024)
Ratio Divergence Learning Using Target Energy in Restricted Boltzmann Machines: Beyond Kullback--Leibler Divergence Learning
by: Ishida, Yuichi, et al.
Published: (2024)
by: Ishida, Yuichi, et al.
Published: (2024)
Adaptive Flip Graph Algorithm for Matrix Multiplication
by: Arai, Yamato, et al.
Published: (2023)
by: Arai, Yamato, et al.
Published: (2023)
Tensor-Network Population Annealing
by: Oshima, Takumi, et al.
Published: (2026)
by: Oshima, Takumi, et al.
Published: (2026)
Toward Architecture-Agnostic Local Control of Posterior Collapse in VAEs
by: Song, Hyunsoo, et al.
Published: (2025)
by: Song, Hyunsoo, et al.
Published: (2025)
Controlling Continuous Relaxation for Combinatorial Optimization
by: Ichikawa, Yuma
Published: (2023)
by: Ichikawa, Yuma
Published: (2023)
Training-Free Time-Series Anomaly Detection: Leveraging Image Foundation Models
by: Namura, Nobuo, et al.
Published: (2024)
by: Namura, Nobuo, et al.
Published: (2024)
Critical Phase Transition in Large Language Models
by: Nakaishi, Kai, et al.
Published: (2024)
by: Nakaishi, Kai, et al.
Published: (2024)
Quantization Error Propagation: Revisiting Layer-Wise Post-Training Quantization
by: Arai, Yamato, et al.
Published: (2025)
by: Arai, Yamato, et al.
Published: (2025)
Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based Sampling
by: Ichikawa, Yuma, et al.
Published: (2024)
by: Ichikawa, Yuma, et al.
Published: (2024)
Continuous Parallel Relaxation for Finding Diverse Solutions in Combinatorial Optimization Problems
by: Ichikawa, Yuma, et al.
Published: (2024)
by: Ichikawa, Yuma, et al.
Published: (2024)
Mutual Information Collapse Explains Disentanglement Failure in $β$-VAEs
by: Vu, Minh, et al.
Published: (2026)
by: Vu, Minh, et al.
Published: (2026)
Continuous First, Discrete Later: VQ-VAEs Without Dimensional Collapse
by: Zhao, Xinyu, et al.
Published: (2026)
by: Zhao, Xinyu, et al.
Published: (2026)
A Testable Certificate for Constant Collapse in Teacher-Guided VAEs
by: Zhang, Zegu, et al.
Published: (2026)
by: Zhang, Zegu, et al.
Published: (2026)
High-Dimensional Learning Dynamics of Quantized Models with Straight-Through Estimator
by: Ichikawa, Yuma, et al.
Published: (2025)
by: Ichikawa, Yuma, et al.
Published: (2025)
Sign Lock-In: Randomly Initialized Weight Signs Persist and Bottleneck Sub-Bit Model Compression
by: Sakai, Akira, et al.
Published: (2026)
by: Sakai, Akira, et al.
Published: (2026)
Beyond Diagonal Covariance: Flexible Posterior VAEs via Free-Form Injective Flows
by: Sorrenson, Peter, et al.
Published: (2025)
by: Sorrenson, Peter, et al.
Published: (2025)
LPCD: Unified Framework from Layer-Wise to Submodule Quantization
by: Ichikawa, Yuma, et al.
Published: (2025)
by: Ichikawa, Yuma, et al.
Published: (2025)
Semantic Rate Distortion and Posterior Design: Compute Constraints, Multimodality, and Strategic Inference
by: Akyol, Emrah
Published: (2026)
by: Akyol, Emrah
Published: (2026)
Posterior Collapse as Automatic Spectral Pruning
by: Hirn, Johannes
Published: (2026)
by: Hirn, Johannes
Published: (2026)
Prior Learning in Introspective VAEs
by: Athanasiadis, Ioannis, et al.
Published: (2024)
by: Athanasiadis, Ioannis, et al.
Published: (2024)
Posterior Collapse as a Phase Transition in Variational Autoencoders
by: Li, Zhen, et al.
Published: (2025)
by: Li, Zhen, et al.
Published: (2025)
A Constrained BA Algorithm for Rate-Distortion and Distortion-Rate Functions
by: Chen, Lingyi, et al.
Published: (2023)
by: Chen, Lingyi, et al.
Published: (2023)
Signs Beat Floats: Low-Rank Double-Binary Adaptation for On-Device Fine-Tuning
by: Fujisawa, Yoshihiko, et al.
Published: (2026)
by: Fujisawa, Yoshihiko, et al.
Published: (2026)
Controlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder Network
by: Kinoshita, Yuri, et al.
Published: (2023)
by: Kinoshita, Yuri, et al.
Published: (2023)
Symmetric Equilibrium Learning of VAEs
by: Flach, Boris, et al.
Published: (2023)
by: Flach, Boris, et al.
Published: (2023)
Improving the Generation of VAEs with High Dimensional Latent Spaces by the use of Hyperspherical Coordinates
by: Ascarate, Alejandro, et al.
Published: (2025)
by: Ascarate, Alejandro, et al.
Published: (2025)
Deep Generative Clustering with VAEs and Expectation-Maximization
by: Adipoetra, Michael, et al.
Published: (2025)
by: Adipoetra, Michael, et al.
Published: (2025)
The Rate-Distortion-Polysemanticity Tradeoff in SAEs
by: Mencattini, Tommaso, et al.
Published: (2026)
by: Mencattini, Tommaso, et al.
Published: (2026)
More Than Bits: Multi-Envelope Double Binary Factorization for Extreme Quantization
by: Ichikawa, Yuma, et al.
Published: (2025)
by: Ichikawa, Yuma, et al.
Published: (2025)
Manifold Learning by Mixture Models of VAEs for Inverse Problems
by: Alberti, Giovanni S., et al.
Published: (2023)
by: Alberti, Giovanni S., et al.
Published: (2023)
Posterior Inference with Diffusion Models for High-dimensional Black-box Optimization
by: Yun, Taeyoung, et al.
Published: (2025)
by: Yun, Taeyoung, et al.
Published: (2025)
Adversarial Robustness of VAEs across Intersectional Subgroups
by: Ramanaik, Chethan Krishnamurthy, et al.
Published: (2024)
by: Ramanaik, Chethan Krishnamurthy, et al.
Published: (2024)
Neural Collapse Dynamics: Depth, Activation, Regularisation, and Feature Norm Threshold
by: Rupa, Anamika Paul
Published: (2026)
by: Rupa, Anamika Paul
Published: (2026)
Commutator-Induced Uncertainty in VAEs
by: Dehdarirad, Tahereh, et al.
Published: (2026)
by: Dehdarirad, Tahereh, et al.
Published: (2026)
Variational Inference: Posterior Threshold Improves Network Clustering Accuracy in Sparse Regimes
by: Li, Xuezhen, et al.
Published: (2023)
by: Li, Xuezhen, et al.
Published: (2023)
Rate-Distortion Optimization for Transformer Inference
by: de Andrade, Anderson, et al.
Published: (2026)
by: de Andrade, Anderson, et al.
Published: (2026)
Training VAEs Under Structured Residuals
by: Dorta, Gara, et al.
Published: (2018)
by: Dorta, Gara, et al.
Published: (2018)
Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss
by: Ziemann, Ingvar, et al.
Published: (2024)
by: Ziemann, Ingvar, et al.
Published: (2024)
An Efficient Algorithm for Thresholding Monte Carlo Tree Search
by: Nameki, Shoma, et al.
Published: (2026)
by: Nameki, Shoma, et al.
Published: (2026)
Similar Items
-
Statistical Mechanics of Min-Max Problems
by: Ichikawa, Yuma, et al.
Published: (2024) -
Ratio Divergence Learning Using Target Energy in Restricted Boltzmann Machines: Beyond Kullback--Leibler Divergence Learning
by: Ishida, Yuichi, et al.
Published: (2024) -
Adaptive Flip Graph Algorithm for Matrix Multiplication
by: Arai, Yamato, et al.
Published: (2023) -
Tensor-Network Population Annealing
by: Oshima, Takumi, et al.
Published: (2026) -
Toward Architecture-Agnostic Local Control of Posterior Collapse in VAEs
by: Song, Hyunsoo, et al.
Published: (2025)