Journal Club

Timing: Friday 10:00 to 12:00 p.m 2021 Spring Semester

Session	Date	Topic	Presenter
1	1/29/2021	[Causal Learning]	Kayhan
2	2/12/2021	[Causal Graph: Hernan and Robins (2019), Chapter 6]	Li, Kayhan
3	3/12/2021	Unmeasured confounders	Brian, Max
4	3/26/2021	Adjustments: Hernan and Robins (2019), Chapter 7	Max, Junxiang
5	4/9/2021	Estimating causal effects: Hernan and Robins (2019), Chapters 11-15	Sumedha, Nihal
6	4/23/2021	Mediation Analysis
7	5/7/2021	Counterfactual: section 3.4	Ke, Rohit
8	5/21/2021	Learning causal graph/structures: Lecture notes	Yanwu
9	6/4/2021	Causal inspired machine learning

Timing: Friday 10:00 to 12:00 p.m 2020 Fall Semester

Session	Date	Topic	Presenter
1	9/11/2020	Self-supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation	Ke
2	9/25/2020	Shapley values for explanation	Sumedha
3	10/9/2020	TDB	Yanwu
4	10/23/2020	MICCAI 2020 Rohit Awards	Rohit
5	10/26/2020	(Special Monday Session) MICCAI 2020 Sumedha/Li/Ke Awards	Sumedha/Li/Ke
6	11/6/2020	Implicit Function	Brian
7	11/20/2020	TDB	Li

2020 Spring Semester

Session	Date	Topic	Presenter
1	1/10/2020	Seeing What a GAN Cannot Generate	Sumedha
2	1/17/2020	Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation	Brian
3	1/24/2020	Diagnosis-Guided Multi-modal Feature Selection for Prognosis Prediction of Lung Squamous Cell Carcinoma	Li
4	1/31/2020	Practice Job Talk	Forough
5	4/3/2020	Weakly Supervised	Yanwu
6	4/10/2020	YOUR CLASSIFIER IS SECRETLY AN ENERGY BASED MODEL AND YOU SHOULD TREAT IT LIKE ONE	Sumedha
7	4/17/2020	Graph NN	Ke
8	4/24/2020	AutoAugment	Brian
9	5/1/2020	AP-Perf: Incorporating Generic Performance Metrics in Differentiable Learning	Juanxiang
10	5/8/2020	Weakly-supervised	Yanwu Xu
11	5/15/2020	Self-supervised	Sun Li
12	5/22/2020	Causal Inference	Sumedha
13	5/29/2020	Equivariant Networks	Rohit
14	6/5/2020	Self-supervised learning for medical image analysis using image context restoration	Ke
15	6/12/2020	Something Applied	Brian
16			Yanwu Xu
17			Sun Li
18	7/31/2020	Deep Image Prior	Rohit

Agenda

2019 Spring Semester

Session	Date	Topic	Presenter
1	08/17/2018	Context: An Algorithm for Determining Negation, Experience, and Temporal Status from Clinical Reports	Sumedha Singla
1	08/17/2018	NegEX:A simple algorithm for identifying negated findings and diseases in discharge summaries.	Sumedha Singla
2	08/24/2018	Empowering Statistical Independence Tests Using Unpaired Data	Mingming Gong
3	08/30/2018	Grad-CAM:Visual Explanations from Deep Networks via Gradient-based Localization	Payman Yadollahpour
4	10/25/2018	Neptune EMR Data Demo	Ke Yu
5	11/01/2018	A Survey on Transfer Learning	Ke Yu
6	11/15/2018	Empowering Statistical Independence Tests Using Unpaired Data	Mingming Gong
7	11/28/2018	Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector	Sumedha Singla
8	11/30/2018	COPD severity prediction and its interpretation with topic modeling	Payman Yadollahpour
9	01/08/2019	GAN DISSECTION: VISUALIZING AND UNDERSTANDING GENERATIVE ADVERSARIAL NETWORKS	Kayhan Batmanghelich
10	01/15/2019	Isolating Sources of Disentanglement in VAEs	Junxiang Chen
11	01/22/2019	SPECTRAL NORMALIZATION FOR GENERATIVE ADVERSARIAL NETWORKS	Yanwu Xu
12	01/29/2019	Poincaré Embeddings for Learning Hierarchical Representations	Ke Yu
13	02/05/2019	Neural Ordinary Differential Equations	Payman Yadollahpour
14	02/26/2019	Hierarchical implicit models and likelihood-free variational inference	Mingming Gong
15	04/09/2019	RL: Markov Decision Process -- Chapter 3	Yuansheng Zhu
16	04/16/2019	RL: Q Learning	Sumedha Singla
17	04/23/2019	RL: Policy Gradient	Payman

2019 Summer Semester

Session	Date	Topic	Presenter
1	06/04/2019	RL: Deep Q Learning and RL revision	Sumedha Singla
2	06/11/2019	RL: Policy Gradient	Payman
3	06/25/2019	RL: Policy Gradient Application	Payman
4	07/02/2019	ICML Debriefing	Junxiang Chen
5	07/09/2019	RL: Inverse RL	Ke Yu
6	07/16/2019	BERT-NLP language modeling	Sumedha
7	07/23/2019	Self Supervised Learning	Brain
8	07/30/2019	Deep Learning in Medical Image Registration: A Survey	Junxiang Chen
9	08/06/2019	Application of ML method on breast mammograms [Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms]	Brain
10	08/13/2019	Survey paper on GAN
11	08/20/2019	Application of ML method on COPD or lung images: 3D GAN	Junxiang Chen
12	08/27/2019	Self-Attention Based Molecule Representation for Predicting Drug-Target Interaction	Ke Yu
13	09/03/2019	Total Airway Count on Computed Tomography and the Risk of Chronic Obstructive Pulmonary Disease Progression. Findings from a Population-based Study	Sumedha Singla

2019 Summer Semester

Session	Date	Topic	Presenter
1	10/15/2019	Bi-GAN	Li
2	10/22/2019	Total Airway Count on Computed Tomography and the Risk of Chronic Obstructive Pulmonary Disease Progression. Findings from a Population-based Study	Sumedha Singla
3	10/29/2019
4	11/05/2019	Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis	Brian
5	11/12/2019	link ASAC: Active Sensing using Actor-Critic models	Ke Yu
6	11/19/2019	Poster and talk	Yanwu
7		Application with few-shot: Learning to Compare: Relation Network for Few-Shot Learning	Yanwu Xu
8		Seeing What a GAN Cannot Generate
9		Learning Data Manipulation for Augmentation and Weighting