New Insights on Reducing Abrupt Representation Change in Online Continual Learning
Github: https://github.com/pclucas14/aml
Paper: https://arxiv.org/abs/2203.03798v1
@ArtificialIntelligencedl
Github: https://github.com/pclucas14/aml
Paper: https://arxiv.org/abs/2203.03798v1
@ArtificialIntelligencedl
Restoring and attributing ancient texts using deep neural networks
Github: https://github.com/deepmind/ithaca
Paper: https://www.nature.com/articles/s41586-022-04448-z
Colab: https://colab.research.google.com/github/deepmind/ithaca/blob/master/colabs/ithaca_inference.ipynb
@ArtificialIntelligencedl
Github: https://github.com/deepmind/ithaca
Paper: https://www.nature.com/articles/s41586-022-04448-z
Colab: https://colab.research.google.com/github/deepmind/ithaca/blob/master/colabs/ithaca_inference.ipynb
@ArtificialIntelligencedl
On Embeddings for Numerical Features in Tabular Deep Learning
Github: https://github.com/yura52/rtdl
Documentatuin: https://yura52.github.io/rtdl
Paper: https://arxiv.org/abs/2203.05556v1
@ArtificialIntelligencedl
Github: https://github.com/yura52/rtdl
Documentatuin: https://yura52.github.io/rtdl
Paper: https://arxiv.org/abs/2203.05556v1
@ArtificialIntelligencedl
GitHub
GitHub - Yura52/rtdl: Research on Tabular Deep Learning (Python package & papers)
Research on Tabular Deep Learning (Python package & papers) - GitHub - Yura52/rtdl: Research on Tabular Deep Learning (Python package & papers)
Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label Enhancement
Github: https://github.com/xuxw98/backtoreality
Paper: https://arxiv.org/abs/2203.05238v1
Dataset: https://paperswithcode.com/dataset/modelnet
@ArtificialIntelligencedl
Github: https://github.com/xuxw98/backtoreality
Paper: https://arxiv.org/abs/2203.05238v1
Dataset: https://paperswithcode.com/dataset/modelnet
@ArtificialIntelligencedl
Conditional Prompt Learning for Vision-Language Models
Github: https://github.com/kaiyangzhou/coop
Paper: https://arxiv.org/abs/2203.05557v1
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
Github: https://github.com/kaiyangzhou/coop
Paper: https://arxiv.org/abs/2203.05557v1
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
Enhancing Adversarial Training with Second-Order Statistics of Weights
Github: https://github.com/alexkael/s2o
Paper: https://arxiv.org/abs/2203.06020v1
Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
Github: https://github.com/alexkael/s2o
Paper: https://arxiv.org/abs/2203.06020v1
Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
Accelerating DETR Convergence via Semantic-Aligned Matching
Github: https://github.com/ZhangGongjie/SAM-DETR
Documentatuin: https://cocodataset.org/
Paper: https://arxiv.org/abs/2203.06883v1
@ArtificialIntelligencedl
Github: https://github.com/ZhangGongjie/SAM-DETR
Documentatuin: https://cocodataset.org/
Paper: https://arxiv.org/abs/2203.06883v1
@ArtificialIntelligencedl
Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine Synergy
Github: https://github.com/davidzhangyuanhan/bamboo
Project: https://opengvlab.shlab.org.cn/bamboo/home
Paper: https://arxiv.org/abs/2203.07845
@ArtificialIntelligencedl
Github: https://github.com/davidzhangyuanhan/bamboo
Project: https://opengvlab.shlab.org.cn/bamboo/home
Paper: https://arxiv.org/abs/2203.07845
@ArtificialIntelligencedl
Context-Aware Drift Detection
Github: https://github.com/SeldonIO/alibi-detect
Project: https://docs.seldon.io/projects/alibi-detect/en/latest/
Paper: https://arxiv.org/abs/2203.08644v1
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
Github: https://github.com/SeldonIO/alibi-detect
Project: https://docs.seldon.io/projects/alibi-detect/en/latest/
Paper: https://arxiv.org/abs/2203.08644v1
Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
➡️ One-Shot Adaptation of GAN in Just One CLIP
A novel single-shot GAN adaptation method through unified CLIP space manipulations.
Github: https://github.com/submission6378/oneshotclip
Paper: https://arxiv.org/abs/2203.09301v1
Dataset: https://paperswithcode.com/dataset/ffhq
Adapted models: https://drive.google.com/drive/folders/1svLJjuuK-yCCJ7Xq9l4Dy4gSuzplK_7i?usp=sharing
@ArtificialIntelligencedl
A novel single-shot GAN adaptation method through unified CLIP space manipulations.
Github: https://github.com/submission6378/oneshotclip
Paper: https://arxiv.org/abs/2203.09301v1
Dataset: https://paperswithcode.com/dataset/ffhq
Adapted models: https://drive.google.com/drive/folders/1svLJjuuK-yCCJ7Xq9l4Dy4gSuzplK_7i?usp=sharing
@ArtificialIntelligencedl
🔹 TensoRF: Tensorial Radiance Fields
A novel approach to model and reconstruct radiance fields
Github: https://github.com/apchenstu/TensoRF
Paper: https://arxiv.org/abs/2203.09517v1
Dataset: https://paperswithcode.com/dataset/ffhq
Project page: https://apchenstu.github.io/TensoRF/
https://t.iss.one/ArtificialIntelligencedl
A novel approach to model and reconstruct radiance fields
Github: https://github.com/apchenstu/TensoRF
Paper: https://arxiv.org/abs/2203.09517v1
Dataset: https://paperswithcode.com/dataset/ffhq
Project page: https://apchenstu.github.io/TensoRF/
https://t.iss.one/ArtificialIntelligencedl
💬 Under the Morphosyntactic Lens: A Multifaceted Evaluation of Gender Bias in Speech Translation
Github: https://github.com/mgaido91/FBK-fairseq-ST
Paper: https://arxiv.org/abs/2203.09866v1
Dataset: https://paperswithcode.com/dataset/winobias
Project page: https://apchenstu.github.io/TensoRF/
@ArtificialIntelligencedl
Github: https://github.com/mgaido91/FBK-fairseq-ST
Paper: https://arxiv.org/abs/2203.09866v1
Dataset: https://paperswithcode.com/dataset/winobias
Project page: https://apchenstu.github.io/TensoRF/
@ArtificialIntelligencedl
🔎 Полное собрание шпаргалок по машинному обучению, статистике, Python и R
Article
@ArtificialIntelligencedl
Article
@ArtificialIntelligencedl
Дзен | Блогерская платформа
Полное собрание шпаргалок по машинному обучению, статистике, Python и R — часть 1
Коллекция шпаргалок, которые помогут вам подготовиться к техническому собеседованию, тестам, презентациям по ds и помогут вам изучить основные концепции науки о данных. Данные шпаргалки помогут вам изучить концепции статистики, синтаксиса языков программирования…
🪄 Generative Invariance Transfer
Github: https://github.com/allanyangzhou/generative-invariance-transfer
Paper: https://arxiv.org/abs/2203.09739v1
Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
Github: https://github.com/allanyangzhou/generative-invariance-transfer
Paper: https://arxiv.org/abs/2203.09739v1
Dataset: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
🚀 AOT (Associating Objects with Transformers for Video Object Segmentation) in PyTorch
Github: https://github.com/yoxu515/aot-benchmark
Paper: https://arxiv.org/pdf/2203.11442v1.pdf
Dataset: https://paperswithcode.com/dataset/davis
Demo: https://github.com/yoxu515/aot-benchmark/blob/main/datasets/Demo
@ArtificialIntelligencedl
Github: https://github.com/yoxu515/aot-benchmark
Paper: https://arxiv.org/pdf/2203.11442v1.pdf
Dataset: https://paperswithcode.com/dataset/davis
Demo: https://github.com/yoxu515/aot-benchmark/blob/main/datasets/Demo
@ArtificialIntelligencedl
📑 PubTables-1M: Towards comprehensive table extraction from unstructured documents
Github: https://github.com/microsoft/table-transformer
Paper: https://arxiv.org/pdf/2110.00061.pdf
Dataset: https://msropendata.com/datasets/505fcbe3-1383-42b1-913a-f651b8b712d3
https://t.iss.one/ArtificialIntelligencedl
Github: https://github.com/microsoft/table-transformer
Paper: https://arxiv.org/pdf/2110.00061.pdf
Dataset: https://msropendata.com/datasets/505fcbe3-1383-42b1-913a-f651b8b712d3
https://t.iss.one/ArtificialIntelligencedl
🦾 Global Tracking Transformers
Github: https://github.com/xingyizhou/GTR
Demo: https://github.com/facebookresearch/detectron2/blob/main/GETTING_STARTED.md
Paper: https://arxiv.org/abs/2203.13250v1
Dataset: https://paperswithcode.com/dataset/mot17
https://t.iss.one/ArtificialIntelligencedl
Github: https://github.com/xingyizhou/GTR
Demo: https://github.com/facebookresearch/detectron2/blob/main/GETTING_STARTED.md
Paper: https://arxiv.org/abs/2203.13250v1
Dataset: https://paperswithcode.com/dataset/mot17
https://t.iss.one/ArtificialIntelligencedl
⚡️ EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation
Github: https://github.com/tjiiv-cprg/epro-pnp
Paper: https://arxiv.org/abs/2203.13254v1
Dataset: https://paperswithcode.com/dataset/nuscenes
@ArtificialIntelligencedl
Github: https://github.com/tjiiv-cprg/epro-pnp
Paper: https://arxiv.org/abs/2203.13254v1
Dataset: https://paperswithcode.com/dataset/nuscenes
@ArtificialIntelligencedl
🎨 Autoregressive Image Generation using Residual Quantization
Github: https://github.com/kakaobrain/rq-vae-transformer
Pytorch: https://github.com/lucidrains/vector-quantize-pytorch
Paper: https://arxiv.org/abs/2203.01941v2
Dataset: https://paperswithcode.com/dataset/lsun
@ArtificialIntelligencedl
Github: https://github.com/kakaobrain/rq-vae-transformer
Pytorch: https://github.com/lucidrains/vector-quantize-pytorch
Paper: https://arxiv.org/abs/2203.01941v2
Dataset: https://paperswithcode.com/dataset/lsun
@ArtificialIntelligencedl
👍2
◾️ pyABC: Efficient and robust easy-to-use approximate Bayesian computation
Github: https://github.com/icb-dcm/pyabc
Paper: https://arxiv.org/abs/2203.13043v1
@ArtificialIntelligencedl
Github: https://github.com/icb-dcm/pyabc
Paper: https://arxiv.org/abs/2203.13043v1
@ArtificialIntelligencedl
👍3
🧍 Discovering Human-Object Interaction Concepts via Self-Compositional Learning
Github: https://github.com/zhihou7/HOI-CL
Paper: https://arxiv.org/abs/2203.14272v1
Dataset: https://paperswithcode.com/dataset/hico-det
@ArtificialIntelligencedl
Github: https://github.com/zhihou7/HOI-CL
Paper: https://arxiv.org/abs/2203.14272v1
Dataset: https://paperswithcode.com/dataset/hico-det
@ArtificialIntelligencedl
👍6