Raising the Cost of AI-Powered Image Editing via Adversarial Perturbations
🖥 Github: https://github.com/madrylab/photoguard
🖥 Colab: https://colab.research.google.com/drive/1pwfeSe6MUjD7UfqdWxurMSWWZhic9TPl?usp=sharing
⏩ Paper: https://arxiv.org/abs/2302.06588v1
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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Espaloma Charge
🖥 Github: https://github.com/choderalab/espaloma_charge
🖥 Colab: https://colab.research.google.com/drive/1e14EkNyidPI0wXBGcewh9m9LC1imSRWZ?usp=sharing
⏩ Paper: https://arxiv.org/abs/2302.06758v1
➡️ Dataset: https://paperswithcode.com/dataset/spice
@ArtificialIntelligencedl
$ pip install espaloma_charge@ArtificialIntelligencedl
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YOWOv2: A Stronger yet Efficient Multi-level Detection Framework for Real-time Spatio-temporal Action Detection
🖥 Github: https://github.com/yjh0410/YOWOv2
⏩ Paper: https://arxiv.org/abs/2302.06848v1
➡️ Dataset: https://paperswithcode.com/dataset/ava
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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Complex-Valued Neural Networks in Keras with Tensorflow
🖥 Github: https://github.com/JesperDramsch/keras-complex
⏩ Paper: https://arxiv.org/abs/2302.08286v1
➡️ Docs: https://keras-complex.readthedocs.io/math.html
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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A Bayesian optimization toolbox built on TensorFlow. Trieste supports onwards and uses semantic versioning.
$ pip install trieste@ArtificialIntelligencedl
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CluCDD:Contrastive Dialogue Disentanglement via Clustering
🖥 Github: https://github.com/gaojingsheng/clucdd
⏩ Paper: https://arxiv.org/abs/2302.08146v1
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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Swapped goal-conditioned offline reinforcement learning
🖥 Github: https://github.com/jasonma2016/gofar
⏩ Paper: https://arxiv.org/abs/2302.08865v1
➡️ Project: https://jasonma2016.github.io/GoFAR/
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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A Survey on Semi-Supervised Semantic Segmentation
🖥 Github: https://github.com/charlesCXK/TorchSemiSeg
⏩ Paper: https://arxiv.org/abs/2302.09899v1
➡️ Dataset: https://paperswithcode.com/dataset/sbd
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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EC-SfM: Efficient Covisibility-based Structure-from-Motion for Both Sequential and Unordered Images
🖥 Github: https://github.com/openxrlab/xrsfm
⏩ Paper: https://arxiv.org/abs/2302.10544v1
➡️ Dataset: https://openxrlab-share.oss-cn-hongkong.aliyuncs.com/xrsfm/test_data.zip?versionId=CAEQQBiBgMCi_6mllxgiIGI2ZjM1YjE1NjBmNTRmYjc5NzZlMzZkNWY1ZTk1YWFj
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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Global Filter Networks for Image Classification
🖥 Github: https://github.com/raoyongming/GFNet
⏩ Paper: https://arxiv.org/abs/2302.10859v1
➡️ Dataset: https://paperswithcode.com/dataset/imagenet
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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RDM: Region-Aware Diffusion for Zero-shot Text-driven Image Editing
🖥 Github: https://github.com/haha-lisa/RDM-Region-Aware-Diffusion-Model
⏩ Paper: https://arxiv.org/abs/2302.11797v1
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective
🖥 Github: https://github.com/microsoft/robustlearn
⏩ Paper: https://arxiv.org/abs/2302.12095v1
➡️ Dataset: https://paperswithcode.com/dataset/advglue
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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Getting more than what you've asked for: The Next Stage of Prompt Hacking
🖥 Github: https://github.com/greshake/lm-safety
⏩ Paper: https://arxiv.org/abs/2302.12173v1
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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SurvivalGAN: Generating Time-to-Event Data for Survival Analysis
🖥 Github: https://github.com/vanderschaarlab/survivalgan
⏩ Paper: https://arxiv.org/abs/2302.12749v1
➡️ Tutorials: https://github.com/vanderschaarlab/synthcity#-tutorials
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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Intepretability for Sequence Generation Models 🔍
🖥 Github: https://github.com/inseq-team/inseq
⏩ Paper: https://arxiv.org/abs/2302.13942v1
💨 Documentation: https://inseq.readthedocs.io
@ArtificialIntelligencedl
pip install inseq@ArtificialIntelligencedl
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Forwarded from ЕЖ
27 февраля стартовал финал совместного профиля «Искусственный интеллект» Национальной технологической олимпиады и Академии искусственного интеллекта для школьников Благотворительного фонда Сбербанка «Вклад в будущее». В него прошли более 100 школьников из 27 регионов России и Казахстана. Всего участников было более 6000. Финальное испытание было подготовлено Sber AI, по итогам профильного тура победители получат возможность пройти оплачиваемую стажировку в Сбере и компаниях-партнерах. В текущем году призовой фонд профиля превышает 4 млн руб.
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FedCLIP: Fast Generalization and Personalization for CLIP in Federated Learning
🖥 Github: https://github.com/microsoft/personalizedfl
⏩ Paper: https://arxiv.org/abs/2302.13485v1
💨 Dataset: https://paperswithcode.com/dataset/office-home
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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Spacerini 🦄
🖥 Github: https://github.com/castorini/hf-spacerini
⏩ Paper: https://arxiv.org/abs/2302.14534v1
@ArtificialIntelligencedl
pip install git+https://github.com/castorini/hf-spacerini.git@ArtificialIntelligencedl
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Interpretable and Intervenable Ultrasonography-based Machine Learning Models for Pediatric Appendicitis
🖥 Github: https://github.com/i6092467/semi-supervised-multiview-cbm
⏩ Paper: https://arxiv.org/abs/2302.14460v1
💨 Dataset: https://paperswithcode.com/dataset/awa2-1
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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Image as Set of Points - ICLR'23 [Oral, Top5%]
🖥 Github: https://github.com/ma-xu/context-cluster
⏩ Paper: https://arxiv.org/abs/2303.01494v1
💨 Dataset: https://paperswithcode.com/dataset/scanobjectnn
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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