Books
- A Sand County Almanac, Aldo Leopold (1949)
- The Cold Start Problem, Andrew Chen (2021)
Papers
- Naturally Occurring Equivariance in Neural Networks, Olah et al., 2020
- High-Low Frequency Detectors, Schubert et al., 2021
- Curve Circuits, Cammarata et al., 2021
- The Building Blocks of Interpretability, Olah et al., 2018
- Visualizing Weights, Voss et al., 2021
- Branch Specialization, Voss et al., 2021
- Weight Banding, Petrov et al., 2021
- Multimodal Neurons in ANNs, Goh et al., 2021
- A Mathematical Framework for Transformer Circuits, Elhage et al., 2021
- Translatotron 3: Speech to Speech Translation with Monolingual Data, Nachmani et al., 2023
- LayerCode: Optical Barcodes for 3D Printed Shapes, Maia et al., 2019
- 3D Gaussian Splatting for Real-Time Radiance Field Rendering, Kerbl et al., 2023
Read and re-implemented for CS510:
- Playing Atari with Deep Reinforcement Learning, Mnih et al., 2013
- Human-Level Control Through Deep Reinforcement Learning, Mnih et al., 2015
- Deep Reinforcement Learning with Double Q-learning, van Hasslet, Guez and Silver., 2015
- Dueling Network Architectures for Deep Reinforcement Learning, Wang et al., 2016
- Rainbow: Combining Improvements in Deep Reinforcement Learning, Hessel et al., 2017
- Deep Reinforcement Learning and the Deadly Triad, Hasselt et al., 2018