| A | B | C | D | E | F | G | H | I | J | K | |
|---|---|---|---|---|---|---|---|---|---|---|---|
1 | DL@MBL 2023 SCHEDULE | ||||||||||
2 | |||||||||||
3 | Lectures (Candle House 104/105) | Exercises (Lillie Library) | Presentations (Candle House 104/105) | Misc | |||||||
4 | |||||||||||
5 | Week 1: Lectures and Exercises | ||||||||||
6 | |||||||||||
7 | 8/21 | 8/22 | 8/23 | 8/24 | 8/25 | 8/26 | 8/27 | 8/28 | |||
8 | Day 0 (Mon) | Day 1 (Tue) | Day 2 (Wed) | Day 3 (Thu) | Day 4 (Fri) | Day 5 (Sat) | Day 6 (Sun) | Day 7 (Mon) | |||
9 | 8:00 AM | ||||||||||
10 | 8:30 AM | ||||||||||
11 | 9:00 AM | Lecture 0: | AUA (Ask Us Anything) | Lecture 4: | AUA (Ask Us Anything) | Lecture 7 / Panel Discussion: | Invited Talk 2: | Day off :) | |||
12 | 9:30 AM | Deep Learning in a Nutshell (Florian Jug) | Continue Exercise 2: | Image Translation | Invited Talk 1: | Failure Modes | Interactive Segmentation (Anna Kreshuk, Constantin Pape) | ||||
13 | 10:00 AM | Lecture 1: | Introduction to DL | (Shalin Mehta) | Interpretable Machine Learning (Assaf Zaritsky) | Continue Exercise 8: | |||||
14 | 10:30 AM | Introduction to ML (David van Valen, remote) | Exercise 4: | Continue Exercise 5: | Exercise 7: | Tracking | |||||
15 | 11:00 AM | Team Assignments | Image Translation | Semantic Segmentation | Failure Modes | ||||||
16 | 11:30 AM | Cloud Setup | |||||||||
17 | 12:00 PM | Lunch (Swope) | Lunch (Swope) | Lunch (Swope) | Lunch (Swope) | Lunch (Swope) | Lunch (Swope) | Lunch (Swope) | |||
18 | 12:30 PM | ||||||||||
19 | 1:00 PM | Exercise 1: | Lecture 3: | Continue Exercise 4: | Lecture 6: | Continue Exercise 7: | Lecture 9: | ||||
20 | 1:30 PM | Introduction to ML | Image Restoration | Image Translation | Instance Segmentation | Failure Modes | Explainable AI and Knowledge Extraction | ||||
21 | 2:00 PM | (Florian Jug + Alex Krull) | (Carsen Stringer/Arlo Sheridan) | (Jan Funke + Diane Adjavon) | |||||||
22 | 2:30 PM | Exercise 3: | Exercise 6: | Exercise 9: | |||||||
23 | 3:00 PM | Image Restoration | Instance Segmentation | Knowledge Extraction | |||||||
24 | 3:30 PM | ||||||||||
25 | 4:00 PM | Arrival and Check-In | Group Picture @ 4:15pm (in front of Lillie) | ||||||||
26 | 4:30 PM | Lecture 2: | Lecture 5: | Lecture 8: | |||||||
27 | 5:00 PM | Introduction to DL | Surprise Talk 1: | Semantic Segmentation | Tracking | ||||||
28 | 5:30 PM | (Jan Funke) | Emma Lundberg (Clapp Auditorium) | (Anna Kreshuk) | (Martin Weigert) | ||||||
29 | 6:00 PM | Dinner (Swope Terrace) | Dinner (Swope) | Dinner (Swope) | Dinner (Swope) | Dinner (Swope) | Dinner (Swope) | Dinner (Swope) | Dinner (Swope) | ||
30 | 6:30 PM | ||||||||||
31 | 7:00 PM | Introduction | Continue Exercise 1: | Continue Exercise 3: | Exercise 5: | Continue Exercise 6: | Exercise 8: | Continue Exercise 9: | |||
32 | 7:30 PM | Introduction to ML | Image Restoration | Semantic Segmentation | Instance Segmentation | Tracking | Knowledge Extraction | ||||
33 | 8:00 PM | Exercise 2: | |||||||||
34 | 8:30 PM | Exercise 0: | Introduction to DL | ||||||||
35 | 9:00 PM | Python Boot Camp | Party in Loeb tent! :) | ||||||||
36 | 9:30 PM | ||||||||||
37 | 10:00 PM | ||||||||||
38 | 10:30 PM | ||||||||||
39 | |||||||||||
40 | |||||||||||
41 | Week 2: Projects | ||||||||||
42 | |||||||||||
43 | 8/29 | 8/30 | 8/31 | 9/1 | 9/2 | 9/3 | 9/4 | 9/5 | |||
44 | Day 8 (Tue) | Day 9 (Wed) | Day 10 (Thu) | Day 11 (Fri) | Day 12 (Sat) | Day 13 (Sun) | Day 14 (Mon) | Day 15 (Tue) | |||
45 | 8:00 AM | ||||||||||
46 | 8:30 AM | ||||||||||
47 | 9:00 AM | Student Data Presentations | Project Kickoff Presentations, Feedback | Invited Talk 4: | Invited Talk 5: | AUA (Ask Us Anything) | AUA (Ask Us Anything) | Invited Talk 6: | Check-Out and Departure | ||
48 | 9:30 AM | (4 mins per student) | Candle House (1-10 mins per project) | Unsupervised Instance Segmentation (Steffen Wolf) | Foundation Models for Microscopy Image Analysis (Constantin Pape) | Web Deployment and Containerization of DL Tools (Beth Cimini) | |||||
49 | 10:00 AM | Optional: Gunpowder Tutorial | AUA (Ask Us Anything) | AUA (Ask Us Anything) | Project Work | Project Work | Project Work | ||||
50 | 10:30 AM | Project Work | Project Work | Project Work | |||||||
51 | 11:00 AM | Project Identification (eight projects) | |||||||||
52 | 11:30 AM | ||||||||||
53 | 12:00 PM | Lunch (Swope) | Lunch (Swope) | Lunch (Swope) | Lunch (Swope) | Lunch (Swope) | Lunch (Swope) | Lunch (Swope) | |||
54 | 12:30 PM | ||||||||||
55 | 1:00 PM | Invited Talk 3: | Project Work | Project Work | Project Work | Project Work | Project Work | Final Project Presentations | |||
56 | 1:30 PM | Behavioral Analysis with Deep Learning (Alex Mathis, remote) | (20 mins per project) | ||||||||
57 | 2:00 PM | Team Assignments (2-4 students, two TAs per two projects) | |||||||||
58 | 2:30 PM | Project Work | |||||||||
59 | 3:00 PM | Problem Formalization, Brainstorming Potential Approach | |||||||||
60 | 3:30 PM | ||||||||||
61 | 4:00 PM | ||||||||||
62 | 4:30 PM | ||||||||||
63 | 5:00 PM | Wrap-Up and Feedback | |||||||||
64 | 5:30 PM | ||||||||||
65 | 6:00 PM | Dinner (Swope) | Dinner (Swope) | Dinner (Swope) | Dinner (Swope) | Dinner (Swope) | Dinner (Swope) | BBQ (Loeb tent) | |||
66 | 6:30 PM | ||||||||||
67 | 7:00 PM | Tutorial 1: | Project Work | Project Work | Project Work | Project Work | Project Work | Party :) | |||
68 | 7:30 PM | Data formats: zarr, ome-zarr (Ziwen Liu) | |||||||||
69 | 8:00 PM | Project Work | |||||||||
70 | 8:30 PM | Discussion: Biases in Machine Learning | |||||||||
71 | 9:00 PM | (Loeb tent) | |||||||||
72 | 9:30 PM | ||||||||||
73 | 10:00 PM | ||||||||||
74 | 10:30 PM | ||||||||||