Artificial Intelligence
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Revolutionizing Chess with Alphazero-like AI
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Reinforcement Learning Made Easy
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Harness the Power of Reinforcement Learning with DIAMBRA Agents
Harness the Power of Reinforcement Learning with DIAMBRA Agents Wouldn’t it be amazing to build agents that can learn to play games on their own? With the DIAMBRA Agents repository, you can do just that. This comprehensive collection of agents is designed to interact seamlessly with DIAMBRA Arena, a suite of Reinforcement Learning environments. Whether…
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Boosting Performance and Efficiency
Scaling AI and Python Applications with Ray: Boosting Performance and Efficiency Artificial intelligence (AI) and Python applications have become increasingly compute-intensive, pushing the limits of single-node development environments. To meet these demands and unlock new levels of scalability, developers need a unified framework that can seamlessly scale their code from a laptop to a cluster.…
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Unlocking Neural Network Training Performance with DeepView.Profile
Unlocking Neural Network Training Performance with DeepView.Profile Are you looking for a way to optimize the training performance of your PyTorch neural networks? Look no further! Introducing DeepView.Profile, a powerful tool designed to profile and debug the performance of PyTorch neural networks. With its intuitive interface and advanced features, DeepView.Profile empowers developers to unleash the…
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A Comprehensive Solution for ML Model Analysis and Profiling
DeepView Explore: A Comprehensive Solution for ML Model Analysis and Profiling DeepView Explore is an advanced tool developed by CentML specifically designed to aid machine learning practitioners in analyzing and profiling their models. This comprehensive solution offers a range of features and functionalities that make it an essential tool in the ML workflow. In this…
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Integrating Probabilistic Logic Programming with Deep Learning
DeepProbLog, developed by the ML-KULeuven research team, is an innovative extension of ProbLog that bridges the gap between probabilistic logic programming and deep learning. By introducing the concept of neural predicates, DeepProbLog leverages neural networks to model and parameterize probabilistic facts. This powerful integration opens up new possibilities for combining symbolic reasoning with data-driven decision…
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Enabling Faster and Accurate Language Processing with AI
Introduction In today’s digital age, the ability to process and understand vast amounts of textual data quickly and accurately is paramount. From customer feedback analysis to information extraction, organizations across industries are constantly seeking more advanced tools and techniques to gain insights from unstructured data. In this article, we introduce FAL (Fast and Accurate Language…
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Automating Machine Learning for Image, Text, Time Series, and Tabular Data
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Extracting Symbolic Knowledge from Sub-symbolic Predictors
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Accurate Post-training Compression for Generative Pretrained Transformers
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Enhancing Machine Learning with Symbolic Knowledge Injection
Machine learning models have revolutionized various applications, from image recognition to natural language processing. However, these models often suffer from limitations such as high memory footprint, data requirements, lack of interpretability, and long training times. Symbolic knowledge injection techniques aim to address these challenges by incorporating prior knowledge into machine learning models. In this article,…
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Demos and Usage Guide
Exploring Symbolic Knowledge Injection with PSyKI: Demos and Usage Guide Symbolic Knowledge Injection (SKI) is a powerful technique that allows us to integrate symbolic reasoning into our data analysis and decision-making processes. With the Python package PSyKI, we can tap into the potential of symbolic knowledge injection and leverage its capabilities to solve complex problems.…
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A Comprehensive Guide
Article: Exporting Deformable Convolution to ONNX in PyTorch: A Comprehensive Guide Artificial intelligence has witnessed significant progress in the field of computer vision, with convolutional neural networks (CNN) playing a crucial role. Deformable convolution is one such innovation that has further improved the performance of CNNs in various computer vision tasks. However, exporting deformable convolutions…
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A Modular and Hackable Transformer Modelling Library for Accelerating Research
xFormers: A Modular and Hackable Transformer Modelling Library for Accelerating Research Transformers have revolutionized the field of natural language processing and have found applications in various domains, including vision and machine translation. However, working with transformers can be complex and time-consuming, especially when implementing bleeding-edge components that are not yet available in mainstream libraries like…
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Revolutionizing Similarity Search and Clustering with Efficient Vector Analysis
As industries become increasingly reliant on complex data analysis, the need for efficient similarity search and clustering algorithms becomes paramount. Faiss, a cutting-edge library developed by Facebook Research, offers a groundbreaking solution to these challenges. With its advanced algorithms and GPU implementation, Faiss enables lightning-fast vector analysis, revolutionizing the way we handle large sets of…
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Advanced Text-to-Speech Generation
In today’s rapidly evolving world, the ability to generate high-quality speech from text is crucial for a wide range of applications. Whether it’s creating voice-overs, virtual assistants, or audiobooks, a robust Text-to-Speech (TTS) solution plays a vital role in enhancing user experiences. Coqui.ai’s TTS library offers advanced features and cutting-edge models that push the boundaries…
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Extracting Meaning from Natural Language
Building Conversational AI with Snips NLU: Extracting Meaning from Natural Language Are you interested in building chatbots or voice assistants? Snips NLU, an open source Python library, could be your go-to tool for extracting structured information from natural language sentences. In this article, we will explore the ins and outs of Snips NLU and how…
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A JVM-Based Deep Learning Ecosystem
Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized various industries, from healthcare to finance and beyond. Deep learning, which is a subset of ML, has emerged as a powerful technique for solving complex problems. Eclipse Deeplearning4J (DL4J) is a cutting-edge deep learning ecosystem built specifically for JVM-based applications. In this article, we will explore…
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Making Deep Learning Accessible for JVM and Android Developers
Deep learning has revolutionized the field of artificial intelligence, enabling machines to learn from vast amounts of data and make intelligent decisions. However, developing and deploying deep learning models has traditionally been a complex and resource-intensive task. KotlinDL, a high-level Deep Learning API written in Kotlin, aims to change that by making deep learning more…