Artificial Intelligence
@ArtificialIntelligencedl
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Artificial Intelligence

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Artificial Intelligence
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Artificial Intelligence
OpenSpike: An OpenRAM SNN Accelerator

🖥 Github: https://github.com/sfmth/openspike

⏩ Paper: https://arxiv.org/abs/2302.01015v1

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Multimodal Chain-of-Thought Reasoning in Language Models

🖥 Github: https://github.com/amazon-science/mm-cot

⏩ Paper: https://arxiv.org/abs/2302.00923v1

➡️ Dataset: https://paperswithcode.com/dataset/scienceqa

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Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning

🖥 Github: https://github.com/NeuralCollapseApplications/FSCIL

⏩ Paper: https://openreview.net/pdf?id=y5W8tpojhtJ

➡️ Dataset: https://paperswithcode.com/dataset/mini-imagenet

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Artificial Intelligence
Tab2KG: Semantic Table Interpretation with Lightweight Semantic Profiles

🖥 Github:https://github.com/sgottsch/tab2kg

⏩ Paper: https://arxiv.org/pdf/2302.01150v1.pdf

➡️ Dataset: https://paperswithcode.com/dataset/dbpedia

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Artificial Intelligence
Top-Down Beats Bottom-Up in 3D Instance Segmentation

🖥 Github: https://github.com/samsunglabs/td3d

⏩ Paper: https://arxiv.org/abs/2302.02871v1

➡️ Dataset: https://paperswithcode.com/dataset/scannet

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Expert Language Models (ELM)

🖥 Github: https://github.com/joeljang/elm

⏩ Paper: https://arxiv.org/abs/2302.03202v1

➡️ Dataset: https://paperswithcode.com/dataset/big-bench

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Artificial Intelligence
Сбер решил сделать подарок всем любителям научного знания и запустил сайт ко Дню российской науки. На сайте можно найти информацию об исследованиях и разработках (R&D) Сбербанка за последние годы.

Также там можно почитать об открытиях и проектах 10 лабораторий Сбера по топовым направлениям науки, в частности:

➡️блокчейн
➡️нейронауки
➡️AR/VR
➡️геймификация
➡️интернет вещей
➡️кибербезопасность
➡️искусственный интеллект

Кроме того можно узнать о партнёрских проектах лабораторий Сбера с ведущими вузами страны и центрами искусственного интеллекта на базе ВШЭ, Сколтеха и МФТИ, присоединиться к мероприятиям, которые проводят исследователи Сбера.

Кому мало, могут посетить специальный проект для всех, кто интересуется наукой.

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Artificial Intelligence
NASiam: Efficient Representation Learning using Neural Architecture Search for Siamese Networks

🖥 Github:https://github.com/aheuillet/nasiam

⏩ Paper: https://arxiv.org/pdf/2302.00059v1.pdf

➡️ Dataset:https://paperswithcode.com/dataset/cifar-100

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Artificial Intelligence
FakeSV: A Multimodal Benchmark with Rich Social Context for Fake News Detection on Short Video Platforms

🖥 Github: https://github.com/ictmcg/fakesv

⏩ Paper: https://arxiv.org/abs/2302.03242v1

➡️ Data Processing: https://github.com/YaoFANGUK/video-subtitle-extractor

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PySlowFast

🖥 Github: https://github.com/facebookresearch/SlowFast

⏩ Paper: https://arxiv.org/abs/2302.04869v1

➡️ Dataset: https://paperswithcode.com/dataset/kinetics-400-1

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Artificial Intelligence
ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills


🖥 Github: https://github.com/haosulab/maniskill2

🖥 Colab: https://colab.research.google.com/github/haosulab/ManiSkill2/blob/main/examples/tutorials/1_quickstart.ipynb

📎 Docs: https://haosulab.github.io/ManiSkill2

⏩ Paper: https://arxiv.org/abs/2302.04659v1

➡️ Dataset: https://paperswithcode.com/dataset/plasticinelab

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Artificial Intelligence
Polynomial Neural Fields for Subband Decomposition and Manipulation

🖥 Github: https://github.com/stevenygd/pnf

⏩ Paper: https://arxiv.org/abs/2302.04862v1

➡️ Dataset: https://paperswithcode.com/dataset/div2k

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Better Diffusion Models Further Improve Adversarial Training

🖥 Github: https://github.com/wzekai99/dm-improves-at

⏩ Paper: https://arxiv.org/abs/2302.04638v1

➡️ Dataset: https://paperswithcode.com/dataset/robustbench

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Artificial Intelligence
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

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Artificial Intelligence
Espaloma Charge

$ pip install 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

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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

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Artificial Intelligence
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

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Artificial Intelligence
✔️ Trieste

A Bayesian optimization toolbox built on TensorFlow. Trieste supports onwards and uses semantic versioning.

$ pip install trieste

🖥 Github: https://github.com/secondmind-labs/trieste

⏩ Paper: https://arxiv.org/abs/2302.08436v1

➡️ Docs: https://secondmind-labs.github.io/trieste

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Artificial Intelligence
CluCDD:Contrastive Dialogue Disentanglement via Clustering

🖥 Github: https://github.com/gaojingsheng/clucdd

⏩ Paper: https://arxiv.org/abs/2302.08146v1

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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/

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