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Project Checkpoint Presentation

Please prepare a Powerpoint presentation which summarizes your group's project and outcomes so far. Use the following format. You should end up with 7+ slides + title.

0. Please identify your team (team name and member names) on a title slide. When you present, be sure to introduce yourselves. Use the team name we have for you in bCourses.

1. (1 slide) Problem statement: What problem you are trying to solve. Should include quality metrics you use to measure performance/accuracy. Don't describe the solution approach (yet).

2. (1 slide) Data source: explain where you got the data. Discuss any preparation or cleaning you did.

3. (2+ slides) Model - Describe your baseline model. Include related work - its fine to use an existing model as the baseline. Explain how your final model will be different.

4. (1 slides) Tools and platform. Describe which tools you used, and which platform (laptop, desktop, EC2 instance etc.). Is the platform adequate for your expected final model?

5. (1+ slide) Baseline results. Give the results for your baseline model on the given dataset.

6. (1 slide) Lessons learned and any challenges you need to overcome for your final model?

Mechanics

Plan to present for 3 minutes. There should be some time for questions in the change-over between groups.

When you're done presenting, disconnect your machine so the next group can present, but stay near the podium to answer questions.

When presenting make sure you have your presentation on a (charged) laptop and also on a backup machine.

Check that your video output works on the projector in 306, and that you know how to use it.

Make sure you know how to manage multiple screens (or to disable that feature) since most laptops map the projector to a different screen by default.

Check that your presentation renders correctly on the target machine. Editing the presentation on windows for presentation on a Mac usually breaks something. pdf will generally render the same on both platforms.

Attendance is compulsory at both presentation sessions.

Submission

Please submit your presentation (the powerpoint or similar file) Here by 10pm on Monday 10/31

Schedule

Monday 10/31

  • AtomEncoder (Tess Smidt)
  • Audio Style Transfer (Davis Foote, Mostafa Rohaninejad, Daylen Yang)
  • Chen/Ju/Fang (Jianbo Chen, Billy Fang, Cheng Ju)
  • Dank Memes (Tony Duan, Wesley Hsieh, YuXuan Liu)
  • Deep RL Locomotion (Stephen Bailey, Will Lin)
  • Deep RNNs (Jason Poulos)
  • DL_Medical_Image_Analysis (Kevin Li, Jiaying Shi)
  • Frame rate upscaling (Gautham Kesineni, Raul Puri, Ted Xiao)
  • JCGAN (Jenny Huang, Cecilia Zhang)
  • J Cubed (Jessica Ko, Jay Patel, James Wei)
  • LearningAtari (Tyler Cheseboro, Aleks Kamko)
  • Marvin/Thanard/Tianhao (Marvin Zhang, Thanard Kurutach, Tianhao Zhang)
  • Murdoch (Jamie Murdoch)
  • RaHan (Raaz Dwivedi, Orhan Ocal)
  • SDC (Raj Agrawal, Sanya Ebrahimi, Martin Nikoltchev, Ashwin Martin)
  • Segmenting RNNs (Aidan Clark, Alon Daks, Daniel Nguyen)
  • WaveNet (Fei Ding, Vinayak Ganeshan, Yunfan Zhang)
  • Baiyu_Chen (Baiyu Chen)

Wednesday 11/2

  • Alexander_Rusciano (Alexander Rusciano)
  • Anurag/Adam (Anurag Ajay, Adam Villafor)
  • BiD.net (Steven Hewitt, An Ju, Katherine Stasaski)
  • CCD (Junyu Cao, Sung-Li Chiang)
  • Deep Color (Xinyang Geng, Angela Lin, Kevin Yu)
  • Deep Dark Learning (Jazlyn Li, Zizheng Tai, Erik Xiong)
  • Deep Drive (Jinkyu Kim, Xinlei Pan, Kiwoo Shin)
  • DeepMARL (Sidney Feygin, Zhiheng Lin)
  • Echochrome (Can Koc, Cem Koc, Brian Su)
  • GnaRLy (Joseph Simonian, Daniel Sochor)
  • Good_Good_Learn (Han Qi, Xuan Zou)
  • Image Captioning (Jingqiu Liu, Jiaqi Xie)
  • Quantum Simulation (Brian Barch)
  • Sequence 2 Sequence (Philippe Laban, Pragaash Ponnusamy, Eldon Schoop)
  • Traffic (Leah Dickstein)
  • VAE (Romain Lopez, Ali Mandani, Allen Tang)
  • Wei/JiaChen/Yeping (Yeping Hu, Jiachen Li, Wei Zhan)
  • WXY (Zining Wang, Zhuo Xu, Bodi Yuan)