Juan Altmayer Pizzorno

2022

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

Papers from Juan Altmayer Pizzorno's perspective

Ordered by how strongly the researchers Juan Altmayer Pizzorno trusts endorse each paper. Same corpus, a different order for every researcher.

1. PyTorch: An Imperative Style, High-Performance Deep Learning Library
2. TensorFlow: A system for large-scale machine learning
3. Vega-Lite: A Grammar of Interactive Graphics
4. Scikit-learn: Machine Learning in Python
5. Guide to NumPy
6. Quantifying the performance of garbage collection vs. explicit memory management
7. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
8. Julia: A Fresh Approach to Numerical Computing
9. Data Structures for Statistical Computing in Python
10. Python: Batteries Included

Their papers

• Triangulating Python Performance Issues with Scalene (2022) — 26 citations