Schedule

Date Lecture Reading Assignments
T Jan 6      
Th Jan 8 Neural Net Basics [slides] [video] DL Book, 6 - 6.2.1.1, 6.3-6.4  
       
T Jan 13 Basics continued [slides] [video] PyTorch Tensors Quiz 1
Th Jan 15 Backpropagation/Implementation [slides] [video 1] [video 2] Backprop for a NN PyTorch intro [video], HW 1: MLP
       
T Jan 20 Physics Informed Neural Nets [slides] [video] PINNs (skim) Quiz 2
Th Jan 22 PINN Implementation [slides] [video] PINN blog post HW 2: Write your own
       
T Jan 27 PINN Wrapup   Quiz 3
Th Jan 29 Optimization Algorithms DL Book Ch 8 HW 3: PINN
       
T Feb 3 Neural ODEs NODE paper, unsteady continuous adjoint, unsteady discrete adjoint Quiz 4
Th Feb 5 Neural ODEs, data   HW 4: PINN inverse
       
T Feb 10 Autoencoders DL book Ch 14 Quiz 5
Th Feb 12 HW help video, GPU video   HW 5: Neural ODE
       
T Feb 17 Monday Instruction   Quiz 6
Th Feb 19 Neural Koopman HW 6: NODE with AE  
       
T Feb 24 Regularization DL Book Ch 7 Quiz 7
Th Feb 26 Convolutional NN   HW 7: Neural Koopman
       
T Mar 3 Convolutional NN DL Book Ch 9  
Th Mar 5 Convolutional NN   Midterm
       
T Mar 10 Graph Networks Math of GNNs Quiz 8
Th Mar 12 Graph Networks PyTorch Geometric HW 8: CNN SuperRes w/ physics
       
T Mar 17 Symbolic Regression PySR Quiz 9
Th Mar 19 Kolmogorov-Arnold KAN paper HW 9: GNN Newtonian Physics
       
T Mar 24 Fourier Neural Operators paper Quiz 10
Th Mar 26 Diffusion Models Medium Post Project Proposal, midterm rework
       
T Mar 31 Recurrent Neural Nets Effectiveness of RNNs Quiz 11
Th Apr 2 Deep RL    
       
T Apr 7 No Class (Transformers videos)   Quiz 12
Th Apr 9 Final Review    
       
T Apr 14 Project Presentations    
Th Apr 16 Project Presentations