Paper Reviews

The list below contains paper reviews I've presented in reverse chronological order of when I reviewed them. These paper reviews were conducted in several different settings. At Bear Flag Robotics, I participated in the deep learning reading group hosted by Blue River Technology. As a Ph.D. student at Auburn University, I participated in the Nguyen Lab weekly meetings where one student either reviewed a paper or presented their own research. Additionally, in the Fall 2020 semester, I took a one-on-one reading course with Hans-Werner Van Wyk in partial fulfillment of my Graduate Minor in Mathematics. I chose "A Survey of Math Through Deep Learning Research" for the theme, so we read deep learning papers that were more mathematical than engineering in flavor, and that spanned several different areas of mathematics. Lastly, in the Fall 2014 semester, I took Statistical Relational Learning and Deep Learning (a seminar course at UT Dallas) taught by Vibhav Gogate where I reviewed a paper. 

• "NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis"

• "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

• "Learning Transferable Visual Models From Natural Language Supervision"

• "Graph WaveNet for Deep Spatial-Temporal Graph Modeling"

• "Big Bird: Transformers for Longer Sequences"

• "Adam: A Method for Stochastic Optimization"

• "Semi-Supervised Classification with Graph Convolutional Networks"

• "Auto-Encoding Variational Bayes"

• "Where Will They Go? Predicting Fine-Grained Adversarial Multi-Agent Motion using Conditional Variational Autoencoders"

• "On the Difficulty of Training Recurrent Neural Networks"

• "Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations"

• "Generalization through Memorization: Nearest Neighbor Language Models"

• "Attributes as Operators: Factorizing Unseen Attribute-Object Compositions"

• "Learning Elementary Structures for 3D Shape Generation and Matching"

• "Image Transformer"

• "Attention Is All You Need"

• "Recurrent World Models Facilitate Policy Evolution"

• "Multi-view 3D Models from Single Images with a Convolutional Network"

• "Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge"

• "Causal Effect Inference with Deep Latent-Variable Models"

• "Deep Content-Based Music Recommendation"