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Starting at York University
Today I’m happy to announce that I’ve started as an Assistant Professor at York University.
Joined the Centre for Vision Research
I am now a member of the Centre for Vision Research at York University.
Introducing cryoSPARC
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.
CNNs for Lung Nodule Classification
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.
Visual Localization with Semantic Cues
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.
Upcoming Travel
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.
Dynamic Texture Synthesis and Style Transfer
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.
Student Volunteer Chair at CVPR 2018
I will be serving as one of the Student Volunteer Chairs for CVPR 2018.
Speaking at 2017 NRAMM Workshop on CryoEM
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.
Area Chair for ECCV 2018
I will be serving as an Area Chair for ECCV 2018.
Joining Borealis AI
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.
Striving for Impact
I wrote a brief essay on striving for impact in research, in particular in machine learning. You can read it on TechVibes here.
Performance Capture Paper at CRV 2018
Our paper on markerless motion capture was accepted for publication at CRV 2018.
Return to Academia
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!
Review article on Normalizing Flows
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.
ICML 2020 Paper on Tail Behaviour of Normalizing Flows
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.
Area Chair for CVPR 2021 and AAAI 2021
I’m happy to announce that I’ll be serving as an Area Chair at CVPR 2021 and AAAI 2021.
Launch of New Website
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.
Two Papers Accepted for 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
Paper and Code for Wavelet Flow
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.
Introduction to Normalizing Flows
This summer I presented a tutorial at ECCV 2020 on normalizing flows with Ullrich Koethe and Carsten Rother. I’ve finally uploaded my lecture which provides an introduction to normalizing flows. Feedback is welcome!
Faculty Affiliate at the Vector Institute
Happy to announce that my Faculty Affiliate status at the Vector Institute has been renewed!
Normalizing Flows Tutorial at CVPR 2021
Happy to announce that Ullrich Koethe and I will be again running our tutorial on Normalizing Flows and Invertible Neural Networks in Computer Vision at CVPR 2021. This will be an updated version of the tutorial we presented at ECCV 2020. The introductory video from that offering is available here. Feel like something should have been presented differently? Want to see more about some other topics? Let me know, feedback is welcome!
Differential Privacy Tutorial (Part 1)
I recently wrote a tutorial on differential privacy. The first part is available now and the second part is coming soon.
First Ontario Workshop on Computer Vision
Proud to announce that I’m serving as the General Chair for the first ever Ontario Workshop on Computer Vision. This is a trainee focused event aiming to provide a forum for computer vision researchers in the province of Ontario to share their early work, network and establish new collaborations. There will be several keynote sessions, poster sessions and more. Keep an eye on the website and OWCV twitter accounts for more information.
Paper Accepted for CVPR 2021
HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color Histograms with Michael Brown and Mahmoud Afifi has been accepted at CVPR 2021. Congratulations and thanks to the student, Mahmoud Afifi, and his supervisor Michael Brown for the fruitful collaboration!
Differential Privacy Tutorial (Part 2)
The second part of my tutorial on differential privacy is now available. The first part was a basic introduction to DP, while part II focuses on using differential privacy in the context of machine learning.
Seminar at UBC
Happy to announce that I will be giving a seminar on Normalizing Flows in Theory and Practice as part of the CAIDA seminar series at the University of British Columbia. For more information and event registration, check out the event announcement. There are likely to be more seminars coming in the near future, keep an eye here for announcements.
Recording of Seminar at UBC
You can find the recording of my seminar on Normalizing Flows in Theory and Practice as part of the CAIDA seminar series at the University of British Columbia here.
Fine-Grained Visual Categorization Workshop Paper at CVPR 2021
Congratulations to my student, Shayan Kousha, whose paper Zero-shot Learning with Class Description Regularization was accepted to the Fine-Grained Visual Categorization Workshop at CVPR 2021. Stay tuned here for more info once the paper is released.
ICML Workshop on Invertible Neural Nets and Normalizing Flows
Happy to annouce that I will be giving an invited talk at the INNF+ Workshop at ICML this year. My collaborators and I also had two papers accepted for presentation at the workshop:
- Manifold Density Estimation via Generalized Dequantization by James A Brofos, Marcus A Brubaker and Roy R Lederman
- Agent Forecasting at Flexible Horizons using ODE Flows by Alexander Radovic, Jiawei He, Janahan Ramanan, Marcus A Brubaker and Andreas Lehrmann (paper to come)
Joining Samsung AI Toronto
I am excited to announce that I have joined the Toronto Samsung AI Center part time as a Visiting Professor. I will be overseeing projects in computer vision and machine learning with their excellent team of researchers. If you’re looking for an industrial position, be sure to check them out!
Recent Preprints and Workshop Papers on arXiv
Several new workshop papers and preprints are now available on arXiv!
- CAMS: Color-Aware Multi-Style Transfer by Mahmoud Afifi, Abdullah Abuolaim, Mostafa Hussien, Marcus A. Brubaker and Michael S. Brown, preprint.
- Continuous Latent Process Flows by Ruizhi Deng, Marcus A. Brubaker, Greg Mori and Andreas Lehrmann at ICML Workshop on Time Series, 2021.
- Manifold Density Estimation via Generalized Dequantization by James A. Brofos, Marcus A. Brubaker and Roy R. Lederman at ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models, 2021.
- Zero-shot Learning with Class Description Regularization by Shayan Kousha and Marcus A. Brubaker at CVPR Workshop on Fine-Grained Visual Categorization, 2021.