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Final Project 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 8+ 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. (1 slide) Baseline Model - Describe your baseline model.

4 (2+ slides) Final Model - explain it clearly, ideally with a diagram. If you explored more than one, please describe each one clearly. Use more slides as needed. Include related work discussion here.

5. (2+ slides) Results - show your results. Include comparison of final model with baseline model, and any competing published models if possible.

5a. (0+ slides) if you think its appropriate, you can do a recorded demo on video. We strongly discourage trying live demos given the time available.

6. (1+ slide) Lessons learned and any challenges you need to overcome for your final model? You can include topics such as tools used, performance.

Mechanics

Plan to present for 5 minutes. There will be time for questions in the change-over between groups.

To expedite the changeover, please upload your submission by 10pm the night before your presentation so we can copy onto a shared laptop. Note that the due date is still 11/27 for all presentations, so this is FYI if you choose to use slip days. It should be in powerpoint. If you use video, please use a common format like wmv or mp4.

If you must use your own laptop, you are responsible for completing your presentation in 5 minutes from the time you reach the podium. There will be no setup time window.

If using your machine:

  • 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 Sunday 11/27

Schedule

Monday 11/28 starting 12:30pm sharp

  • 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)

Wednesday 11/30 starting 12:30pm sharp

  • 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)