Journal Club

Every fortnight, we host a casual machine learning journal club session at 2pm in M-Wing. If you would like to be added to the mailing list, please email me directly.

Upcoming

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Date	Presenter	Topic
16 March 2020	Wenchao Han	Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
30 March 2020	Geoff Klein	—
27 April 2020	Chetan	—

Previous

[tabby title=”2020″]

Date	Presenter
08 June 2020	—	Slot Available
25 May 2020	—	Slot Available
11 May 2020	Jianan Chen	—
27 April 2020	Chetan	—
30 March 2020	Geoff Klein	—
16 March 2020	Wenchao Han	Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
24 Feb 2020	Cem Anil	Introduction to Capsule Networks
20 Jan 2020	Grey Kuling	Generalizing Deep Models for Ultrasound Image Segmentation

Previous

[tabby title=”2019″]

Date	Presenter
9 Dec 2019	David Burns	FaceNet: A Unified Embedding for Face Recognition and Clustering
25 Nov 2019	Chetan Srinidhi	Self-supervised learning for medical image analysis using image context restoration
11 Nov 2019	Ahmed Harouni (Guest, NVidia)	NVIDIA CLARA Intelligent Compute Engine for Healthcare and Life Sciences
28 Oct 2019	Anne Martel	Deep Clustering with Convolutional Autoencoders | Improved Deep Embedded Clustering with Local Structure Preservation
30 Sept 2019	Michael Hardisty	Combining learned and analytical models for predicting action effects from sensory data
19 Aug 2019	Griffin Lacey (guest, NVidia)	Using the NVIDIA software stack for Deep Learning
22 July 2019	Jun Ma	Boundary loss for highly unbalanced segmentation | presentation
8 July 2019	Jianan Chen	ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
3 June 2019	Ozan Ciga	A DIRT-T Approach to Unsupervised Domain Adaptation | presentation
27 May 2019	Andrei Mouraviev	Troubling Trends in Machine Learning Scholarship | presentation
13 May 2019	David Burns	Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks | presentation
29 April 2019	Nikhil Seth	Micro-Net: A unified model for segmentation of various objects in microscopy images
15 April 2019	Linde Hesse	Style Augmentation: Data Augmentation via Style Randomization | presentation
1 April 2019	Shazia Akbar	Semi Supervised Classification with Graph Convolutional Networks | presentation

[tabby title=”2018″]

Date	Presenter
26 November 2018	Alex Lu (Guest)	Discovering biological insights from large-scale microscopy datasets with unsupervised deep learning
12 November 2018	Wenchao Han (Guest)	Automatic prostate cancer detection and grading on histopathology using machine learning
29 October 2018	Matthew Ng	A Probabilistic U-Net for Segmentation of Ambiguous Images
15 October 2018	Anne Martel	MICCAI 2018 Review | link to webpage
20 August 2018	Grey Kuling	Application of reinforcement learning for segmentation of transrectal ultrasound images
23 July 2018	David Madras (Guest)
14 May 2018	Grey Kuling	Binary Classifier Evaluation Without Ground Truth | presentation
16 April 2018	Shazia Akbar	Recurrent Models of Visual Attention | presentation
19 March 2018	David Burns	Synthetic Data Augmentation using GAN for Improving Liver Lesion Classification | presentation
5 March 2018	Andrei Mouraviev	Recurrent Neural Networks tutorial | presentation
5 February 2018	Nikhil Seth	Cost curves: An improved method for visualizing classifier performance | presentation

[tabby title=”2017″]

11 December 2017	Shazia Akbar	Marginal Space Deep Learning: Efficient Architecture for Volumetric Image Parsing | presentation
27 November 2017	Michael Hardisty	Marginal Shape Deep Learning: Applications to Pediatric Lung Field Segmentation | presentation
13 November 2017	Anne Martel	Predicting cancer outcomes from histology and genomics using convolutional networks | presentation
30 October 2017	Nikhil Seth	Natural Language Processing for Classification of Acute, Communicable Findings on Unstructured Head CT Reports: Comparison of Neural Network and Non-Neural Machine Learning Techniques | presentation
16 October 2017	Daniel Eftekhari	Object Recognition and Segmentation – from R-CNN to Mask R-CNN | presentation
2 October 2017	Matthew Ng	Deep Watershed Transform for Instance Segmentation
18 September 2017	Andrei Mouraviev
21 August 2017	Tina Wu, Jason Leung	Explaining the Unexplained: A CLass-Enhanced Attentive Response (CLEAR) Approach to Understanding Deep Neural Networks, Convolutional Pose Machines
24 July 2017	Normand Robert	Artificial intelligence and the future of work
10 July 2017	Nikhil Seth	Understanding deep learning requires re-thinking generalization
26 June 2017	Shazia Akbar	Zoom-in-Net: Deep Mining Lesions for Diabetic Retinopathy Detection | presentation
29 May 2017	Michael Hardisty	PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
15 May 2017	Invited Speaker: Julia Schnabel	Computational imaging in cancer
3 April 2017	Shazia Akbar	TUTORIAL: Designing Deep Architectures | presentation | code A practical theory for designing very deep convolutional neural networks
6 March 2017	Anne Martel	Using Deep Learning to Segment Breast and Fibroglanduar Tissue in MRI Volumes
6 February 2017	Santosh Hariharan	Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records
23 January 2017	Shazia Akbar	Rethinking the Inception Architecture for Computer Vision | presentation
9 January 2017	2017 Welcome!
12 December 2016	Mehrdad Gangeh	Semi-supervised Dictionary Learning Based on Hilbert-Schmidt Independence Criterion
14 November 2016	Sylvester Chang	Learning deconvolution network for semantic segmentation
31 October 2016	Masoud Hashemi	A General Framework for Context-Specific Image Segmentation Using Reinforcement Learning
17 October 2016	Pitches and Lasagne demo	Link to python code and libraries

[tabbyending]

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