Kris Ganjam

AllenInstitute/GRNN: GRNN v1.0.0 — Differentiable biologically-derived single-neuron models

Calvin Yeung, Zhixin Lu, Kris Ganjam

Code and data accompanying Yeung et al., "A dataset of differentiable biologically-derived single neuron models" (Cell Reports Methods, 2026). This release provides: A database of over 1,000 fitted single-neuron firing-rate (GFR) model parameter sets, with per-cell provenance metadata (cell ID, Cre line, …

gb (code pays fourni par la source)

AllenInstitute/GRNN: GRNN v1.0.0 — Differentiable biologically-derived single-neuron models

Calvin Yeung, Zhixin Lu, Kris Ganjam

Code and data accompanying Yeung et al., "A dataset of differentiable biologically-derived single neuron models" (Cell Reports Methods, 2026). This release provides: A database of over 1,000 fitted single-neuron firing-rate (GFR) model parameter sets, with per-cell provenance metadata (cell ID, Cre line, …

gb (code pays fourni par la source)

AllenInstitute/GRNN: GRNN: Differentiable Biologically-Derived Single-Neuron Models

Calvin Yeung, Zhixin Lu, Kris Ganjam

GRNN v1.0.0 — Differentiable biologically-derived single-neuron models Code and data accompanying Yeung et al., "A dataset of differentiable biologically-derived single neuron models" (Cell Reports Methods, 2026). This release provides: A database of over 1,000 fitted single-neuron firing-rate (GFR) model parameter sets, with …

gb (code pays fourni par la source)

Multiregional single-cell profiling reveals shared and specialized cellular vulnerability in Alzheimer’s disease

Kyle J. Travaglini, Mariano I. Gabitto, Yi Ding, Anamika Agrawal et autres

Abstract Alzheimer’s disease (AD) is defined and staged by the stereotyped, progressive accumulation of amyloid-beta (Aβ) plaques and hyperphosphorylated tau (pTau) tangles across brain regions. These regions differ substantially in their architecture and function but share largely conserved cellular composition, with some …

us, gb (code pays fourni par la source)

A dataset of differentiable biologically-derived single neuron models

Calvin Yeung, Zhixin Lu, Kris Ganjam, Ştefan Mihalaş

Abstract Biological neural networks contain diverse cell types with heterogeneous electrophysiological properties. Artificial neural networks (ANNs) model computational aspects of biology but use homogeneous neurons, limiting realism. A key obstacle to building bio-inspired ANNs is the absence of a database of neuron …

us (code pays fourni par la source)

Transform-data-by-example (TDE)

Yeye He, Xu Chu, Kris Ganjam, Yudian Zheng et autres

Today, business analysts and data scientists increasingly need to clean, standardize and transform diverse data sets, such as name, address, date time, and phone number, before they can perform analysis. This process of data transformation is an important part of data preparation, …

gb, us, in (code pays fourni par la source)

Transform-Data-by-Example (TDE)

Yeye He, Kris Ganjam, Kukjin Lee, Yue Wang et autres

Business analysts and data scientists today increasingly need to clean, standardize and transform diverse data sets, such as name, address, date time, phone number, etc., before they can perform analysis. These ad-hoc transformation problems are typically solved by one-off scripts, which is …

us (code pays fourni par la source)

Discovering Enterprise Concepts Using Spreadsheet Tables

Keqian Li, Yeye He, Kris Ganjam

Existing work on knowledge discovery focuses on using natural language techniques to extract entities and relationships from textual documents. However, today relational tables are abundant in quantities, and are often well-structured with coherent data values. So far these rich relational tables have …

us (code pays fourni par la source)

An Insight Extraction System on BioMedical Literature with Deep Neural Networks

Hua He, Kris Ganjam, Navendu Jain, Jessica Lundin et autres

Mining biomedical text offers an opportunity to automatically discover important facts and infer associations among them.As new scientific findings appear across a large collection of biomedical publications, our aim is to tap into this literature to automate biomedical knowledge extraction and identify …

us, gb, ca (code pays fourni par la source)

Data services leveraging Bing's data assets.

Kaushik Chakrabarti, Surajit Chaudhuri, Zhimin Chen, Kris Ganjam et autres

Web search engines like Bing and Google have amassed a tremendous amount of data assets. These include query-click logs, web crawl corpus, an entity knowledge graph and geographic/maps data. In the Data Management, Exploration and Mining (DMX) group at Microsoft Research, we …

SEMA-JOIN

Yeye He, Kris Ganjam, Xu Chu

Join is a powerful operator that combines records from two or more tables, which is of fundamental importance in the field of relational database. However, traditional join processing mostly relies on string equality comparisons. Given the growing demand for ad-hoc data analysis, …

us, ca (code pays fourni par la source)

TEGRA

Xu Chu, Yeye He, Kaushik Chakrabarti, Kris Ganjam

It is well known today that pages on the Web contain a large number of content-rich relational tables. Such tables have been systematically extracted in a number of efforts to empower important applications such as table search and schema discovery. However, a …

ca, us (code pays fourni par la source)