John Hunter, the author of matplotlib passed away yesterday after a short battle against cancer. John gave the keynote at the scipy 2012 conference a few weeks ago, and was diagnosed with cancer just on his return from the conference. It is a shock to me that that a friend can disappear so quickly. Please [...]
Archive for the 'computational science' Category
Open research computation (ORC) was an attempt to create a scientific publication promoting high-quality and open source scientific code. The project went public in falls 2010, but last month, facing the low volume of submission, the editorial board chose to reorient it as a special track of an existing journal.
The challenges that we face [...]
The scikit-learn got 3 students accepted for the Google summer of code.
Imanuel Bayer will work on making our sparse linear models, for regression and classification, faster. His proposal Optimizing sparse linear models using coordinate descent and strong rules.
David Marek will implement multi-layer perceptrons for the scikit. His proposal: Multilayer Perceptron
Vlad Niculae will work on speeding [...]
Lately, I have been a mood of scientific scepticism: I have the feeling that the worldwide academic system is more and more failing to produce useful research. Christophe Lalanne’s twitter feed lead me to an interesting article in a non-mainstream journal: A farewell to Bonferroni: the problems of low statistical power and publication bias, [...]
Packt publishing sent me a copy of NumPy 1.5 Beginner’s guide by Ivan Idris.
The book actually covers more than only numpy: it is a full introduction to numerical computing with Python. The table of contents is the following:
NumPy Quick Start
Beginning with NumPy Fundamentals
Get into Terms with Commonly Used Functions
Convenience Functions for Your Convenience
Working with Matrices [...]
Top notch scientific conferences are starting to add Python tracks to their program. This is good news. Indeed, it scientific Python conferences (namely Scipy, EuroSciPy and Scipy India) are doing great to get together people who have already heard about Python for science, but we need to reach out to specific Python communities to maximize [...]
At the request of a friend, I am putting up some of the posters that I recently presented at conferences.
Large-scale functional-connectivity graphical models for individual subjects using population prior.
This is a poster for our NIPS work
Multi-subject dictionary learning to segment an atlas of brain spontaneous activity.
This is a poster for our IPMI work
Mayavi for 3D [...]
The Scipy 2011 conference in Austin
Last week, I was at the Scipy conference in Austin. It was really great to see old friends, and Austin is such a nice place.
The Scipy conference was held in UT Austin’s conference center, which is a fantastic venue. This is the first geek’s conference I have been at where [...]
The scikits.learn is a Python module for machine learning. The project builds on the scientific and numerical tools of the scipy community to provide state-of-the-art data analysis tools. It is developed by a community of open source developers to which my research team (Parietal, INRIA) contributes a lot and is a striving project. Its mailing [...]
Submission deadline May 8th
The deadline for the call for presentation for the EuroScipy conference is on May 8th. There is only a week and a half left.
EuroScipy will be held in Paris, August 25-28. It is the European meeting for users of Python in scientific and numerical-intensive applications. It strives to bring together both users [...]