Jasmine T. Stone

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it
• Cognitive Neuroscience — 12 citations into it
• Probabilistic & Bayesian Methods — 12 citations into it
• Cellular and Molecular Neuroscience — 9 citations into it
• Computational Theory and Mathematics — 7 citations into it
• Electrical and Electronic Engineering — 6 citations into it

Whom Jasmine T. Stone trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. David John Cameron MacKay
2. John P. Cunningham
3. Andrew Gordon Wilson
4. James Hensman

Papers from Jasmine T. Stone's perspective

Ordered by how strongly the researchers Jasmine T. Stone trusts endorse each paper. Same corpus, a different order for every researcher.

1. Information Theory, Inference, and Learning Algorithms
2. Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP)
3. Scalable Variational Gaussian Process Classification
4. Reorganization between preparatory and movement population responses in motor cortex (Nature Communications)
5. Linear dynamical neural population models through nonlinear embeddings
6. Dimensionality reduction for large-scale neural recordings
7. Suite2p: beyond 10,000 neurons with standard two-photon microscopy (bioRxiv)
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet classification with deep convolutional neural networks

Their papers

• Scalable Bayesian GPFA with automatic relevance determination and discrete noise models (2021) — 21 citations