IEEE

Autoencoder Architectures for Low-Rate Sparse Point Cloud Geometry Coding

Abstract: Efficient compression of sparse point cloud geometry remains a critical challenge in 3D content processing, particularly for low-rate scenarios where conventional codecs struggle to maintain ...
VentureBeat

DeepMind makes big jump toward interpreting LLMs with sparse autoencoders

Large language models (LLMs) have made remarkable progress in recent years. But understanding how they work remains a challenge and scientists at artificial intelligence labs are trying to peer into ...
Visual Studio Magazine

Data Dimensionality Reduction Using a Neural Autoencoder with C#

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on creating an approximation of a dataset that has fewer columns. Imagine that you have a dataset that has many ...
IEEE

Dual-Constraint Autoencoder and Adaptive Weighted Similarity Spatial Attention for Unsupervised Anomaly Detection

Abstract: Image reconstruction-based methods with autoencoder have been widely used for unsupervised anomaly detection. By training the reconstruction on normal ...
C&EN

Protein Ensemble Generation Through Variational Autoencoder Latent Space Sampling

Department of Biochemistry, University of Washington, Seattle, Washington 98195, United States Institute for Protein Design, University of Washington, Seattle, Washington 98195, United States ...
GitHub

No module named 'pytorch_lightning'

File "C:\Users\stable\ComfyUI\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI-Stable-Video-Diffusion\nodes.py", line 56, in load_svd_model self.svd_model = load ...