The Bookshelf
some past reads I found interesting.
Technical Literature
☞ Cinematic Mindscapes: High-quality Video Reconstruction from Brain Activity (NeurIPS 2024)☞ LoRA: Low-Rank Adaptation of Large Language Models (ICLR 2022)
☞ QLORA: Efficient Finetuning of Quantized LLMs (NeurIPS 2023)
☞ Voyager: An Open-Ended Embodied Agent with Large Language Models (TMLR 2024)
☞ ChatDev: Communicative Agents for Software Development (arXiv 2023)
☞ 3D Gaussian Splatting for Real-Time Radiance Field Rendering (Graph 2023)
☞ NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis (ECCV 2020)
☞ ResNET: Deep residual learning for image recognition (IEEE 2016)
☞ RNNs: Sequence to Sequence Learning with Neural Networks (NeurIPS 2014)
☞ Transformer: Attention Is All You Need (NeurIPS 2017)
☞ Show, Attend and Tell: Neural Image Caption Generation with Visual Attention (PMLR 2015)
☞ Word2Vec: Efficient estimation of word representations in vector space (Google 2013)
☞ COT: Chain-of-Thought Prompting Elicits Reasoning in Large Language Models (NeurIPS 2022)
☞ RAG: Retrieval-Augmented Generation for Large Language Models: A Survey (arXiv 2023)
☞ Parameter-Efficient Transfer Learning for NLP (PMLR 2019)
☞ AlexNet: ImageNet Classification with Deep Convolutional Neural Networks (NeurIPS 2012)
☞ UNet:U-net: Convolutional networks for biomedical image segmentation (MICCAI 2015)
☞ An image is worth 16x16 words: Transformers for image recognition at scale (ICLR 2021)
☞ Context encoders: Feature learning by inpainting (CVPR 2016)
☞ MAEs: Masked Autoencoders Are Scalable Vision Learners (CVPR 2022)
☞ GANs: Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks (arXiv 2015)
☞ CLIP: Learning Transferable Visual Models From Natural Language Supervision (PMLR 2021)
☞ Denoising Diffusion Probabilistic Models (NeurIPS 2020)
☞ High-Resolution Image Synthesis with Latent Diffusion Models (CVPR 2022)
☞ Denoising Diffusion Models: A Generative Learning Big Bang (CVPR 2023)
☞ Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack (Meta 2023)
☞ ControlNet: Adding Conditional Control to Text-to-Image Diffusion Models (ICCV 2023)
☞ Listen, Think, and Understand (ICLR 2024)