Search Results for author:
Found 7 papers, 6 papers with code
MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs
Training LLMs at this scale brings unprecedented challenges to training efficiency and stability.
Video-CSR: Complex Video Digest Creation for Visual-Language Models
We present a novel task and human annotated dataset for evaluating the ability for visual-language models to generate captions and summaries for real-world video clips, which we call Video-CSR (Captioning, Summarization and Retrieval).
Revisiting Multimodal Representation in Contrastive Learning: From Patch and Token Embeddings to Finite Discrete Tokens
However, direct aligning cross-modal information using such representations is challenging, as visual patches and text tokens differ in semantic levels and granularities.
Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE
Specifically, we propose to construct latent variable models of neural activity while simultaneously modeling the relation between the latent and task variables (non-neural variables, e. g. sensory, motor, and other externally observable states).
A zero-inflated gamma model for deconvolved calcium imaging traces
However, statistical modeling of deconvolved calcium signals (i. e., the estimated activity extracted by a pre-processing pipeline) is just as critical for interpreting calcium measurements, and for incorporating these observations into downstream probabilistic encoding and decoding models.
Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov Model
The Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) has been used widely as a natural Bayesian nonparametric extension of the classical Hidden Markov Model for learning from sequential and time-series data.
Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data
Calcium imaging has revolutionized systems neuroscience, providing the ability to image large neural populations with single-cell resolution.
