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Recommended Machine Learning Papers and Learning Resources

miguelmartin.com · published 28 March 2024

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https://arxiv.org/pdf/2211.04325.pdf
arxiv.org
https://arxiv.org/abs/2206.14486
arxiv.org
https://proceedings.neurips.cc/paper_files/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf
proceedings.neurips.cc
https://arxiv.org/abs/1711.07971
arxiv.org
https://arxiv.org/abs/1706.03762
arxiv.org
https://arxiv.org/abs/1512.03385
arxiv.org
https://arxiv.org/abs/2010.11929
arxiv.org
https://paperswithcode.com/method/resnext-block
paperswithcode.com
https://arxiv.org/abs/2104.11227
arxiv.org
https://arxiv.org/abs/2102.05095
arxiv.org
https://arxiv.org/abs/2105.08050
arxiv.org
https://arxiv.org/abs/2111.06377
arxiv.org
https://arxiv.org/abs/2203.12602
arxiv.org
https://github.com/facebookresearch/AudioMAE
github.com
https://weichen582.github.io/diffmae.html
weichen582.github.io
https://github.com/facebookresearch/omnivore
github.com
https://imagebind.metademolab.com/
imagebind.metademolab.com
https://github.com/facebookresearch/maws
github.com
https://paperswithcode.com/method/dino
paperswithcode.com
https://arxiv.org/abs/2301.11320
arxiv.org
https://arxiv.org/abs/2308.14710
arxiv.org
https://ai.meta.com/research/publications/revisiting-feature-prediction-for-learning-visual-representations-from-video/
ai.meta.com
https://arxiv.org/pdf/2403.15377.pdf
arxiv.org
https://arxiv.org/abs/2304.12210
arxiv.org
https://arxiv.org/abs/1809.11096
arxiv.org
https://mingukkang.github.io/GigaGAN/
mingukkang.github.io
https://arxiv.org/abs/2006.11239
arxiv.org
https://sander.ai/2022/01/31/diffusion.html
sander.ai
OpenAI’s DALL·E 2 Read at the source ↗
openai.com
https://cdn.openai.com/papers/dall-e-3.pdf
cdn.openai.com
Imagen Read at the source ↗
imagen.research.google
https://research.nvidia.com/labs/rtr/neural_texture_compression/
research.nvidia.com
https://research.nvidia.com/labs/toronto-ai/compact-ngp/
research.nvidia.com
https://cmsc426.github.io/sfm/
cmsc426.github.io
https://arxiv.org/abs/2003.08934
arxiv.org
https://github.com/google/mipnerf
github.com
https://github.com/NVlabs/instant-ngp
github.com
https://bmild.github.io/rawnerf/
bmild.github.io
https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/
repo-sam.inria.fr
https://guanjunwu.github.io/4dgs/
guanjunwu.github.io
https://segment-anything.com/
segment-anything.com
https://github.com/hkchengrex/XMem
github.com
https://github.com/gaomingqi/Track-Anything
github.com
https://github.com/ViTAE-Transformer/ViTPose
github.com
https://arxiv.org/pdf/1905.05055.pdf
arxiv.org
https://openai.com/research/clip
openai.com
https://paperswithcode.com/task/adversarial-robustness
paperswithcode.com
https://arxiv.org/abs/2303.15343
arxiv.org
https://arxiv.org/abs/2403.09611
arxiv.org
https://llava-vl.github.io/
llava-vl.github.io
https://arxiv.org/pdf/2204.02311.pdf
arxiv.org
https://openai.com/research/gpt-2-1-5b-release
openai.com
https://arxiv.org/abs/2302.13971
arxiv.org
https://arxiv.org/abs/2307.09288
arxiv.org
https://arxiv.org/abs/2312.11805
arxiv.org
https://github.com/LAION-AI/CLAP
github.com
https://github.com/ggerganov/llama.cpp
github.com
https://github.com/ggerganov/ggml
github.com
https://github.com/karpathy/nanoGPT
github.com
https://github.com/monatis/clip.cpp
github.com
https://github.com/Lightning-AI/litgpt
github.com
https://github.com/cybertronai/gradient-checkpointing
github.com
LAION-5B Read at the source ↗
laion.ai
https://github.com/google-research-datasets/conceptual-12m
github.com
https://github.com/facebookresearch/Ego4d/
github.com
https://www.deeplearningbook.org/
deeplearningbook.org
https://arxiv.org/pdf/2403.18103.pdf
arxiv.org
https://localrf.github.io/
localrf.github.io