The code and paper for our NeurIPS 2020 paper, Wavelet Flow: Fast Training of High Resolution Normalizing Flows, is now available. The code is availble through the Wavelet Flow GitHub Project. The paper can be found on arXiv. All of this, and additional image results, can be found on the Wavelet Flow Project Page. If you have questions, feel free to get in touch or check us out at our poster session at NeurIPS 2020.
Two papers on normalizing flows have been accepted at NeurIPS 2020. Congratulations and thanks to the students, Jason and Ruizhi, and my excellent collaborators!
- Wavelet Flow: Fast Training of High Resolution Normalizing Flows with Jason Yu and Konstantinos Derpanis (arxiv preprint to come)
- Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows with Ruizhi Deng, Bo Chang, Greg Mori and Andreas Lehrmann
I’ve finally launched a new website based on GitHub Pages. This should make it easier for me to maintain and add content. Keep an eye on things over the coming weeks as I work to expand and improve its contents. My old York EECS website is still availble here and my ancient UofT DCS website is still available here, although I am planning to take down my DCS page soon.
Our paper on the “Tails of Lipschitz Triangular Flows” has been accepted for publication at ICML 2020. If you’re attending, be sure to stop by and chat.
I recently co-authored a review article (preprint version) on Normalizing Flows which will be published in IEEE Transactions of Pattern Analysis and Machine Intellgience. Normalizing Flows is a topic that I’m excited about and looking to work more on in the future. If you’ve not seen it before, please check it out.
I have returned full time to academia! At the moment I am working on expanding my lab and restarting my research program. Watch this space for updates in the near future!
I wrote a brief essay on striving for impact in research, in particular in machine learning. You can read it on TechVibes here.
I am excited to announce that I will be joining Borealis AI as a Researcher Director. This will be part time for now and become full time starting May 1st, when I take a leave of absence from my position at York University. Read more about Borealis and the work I’ll be doing there here.
I will be speaking on “Bayesian Methods in Cryo-EM” at the 2017 NRAMM Workshop on Advanced Topics in EM Structure Determination: Challenges and Opportunities.
I will be serving as one of the Student Volunteer Chairs for CVPR 2018.
Our new paper on dynamic textures is now available on arXiv here and the website with more results and details can be found here. Also, I’ll be attending CVPR in July. If you’re going to be there and would like to meet up, feel free to drop me an email.
I also recently visited the Program in Applied and Computational Mathematics at Princeton University to deliver the IDeAS Seminar on April 27th. I’ll next be visiting and speaking at several places in Montreal and Lausanne this month. Feel free to say hello!
- May 10th - Speaking at the Canadian Microscopy and Cytometry Symposium in Montreal. See the symposium website for the presentation schedule.
- May 12th - Visiting Joaquin Ortega and Kaleem Sadiqqi at McGill University in Montreal. I’ll be giving a seminar for a computer science audience in the afternoon.
- May 15th - Speaking at the 2017 Cryo-EM Symposium at EPFLs BioEM Facility in Lausanne, Switzerland
- May 16th - Visiting the CVLab at EPFL. I’ll be giving a computer science oriented seminar in the morning.
Recent work on using semantic cues to localize a vehicle will be presented at the 2017 IEEE International Conference on Robotics and Automation (ICRA). This is joint work with Wei-Chui Ma, Shenlong Wang, Sanja Fidler and Raquel Urtasun. You can find the paper here and a video of some of the results here.
Paper at the 2017 IEEE Winter Conference on Applications of Computer Vision (WACV) on predicting the malignancy of lung nodules in CT scans with 3D convolutional neural networks. Find the paper here.
A major focus of my research over the last few years as been into new methods for the determination of 3D structures of viruses and proteins. A big piece of that work has been published today in Nature Methods. This article describes the algorithmic advances which underpin cryoSPARC. This work was done in collaboration with Ali Punjani (PhD Student, University of Toronto), John Rubinstein (Senior Research Scientist, Hospital for Sick Children) and David Fleet (Professor, University of Toronto).
For a non-technical introduction to our work, you can take a look at this story out of University of Toronto, Scarborough.
I am now a member of the Centre for Vision Research at York University.