[R] Should I still write up my clinical ML project if the results aren’t “amazing”? Metrics in body!!
🎵Audio ML
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Beyond Brute Force: 4 Secrets to Smaller, Smarter, and Dramatically Cheaper AI
hackernoon.com·1d
🕵️Vector Smuggling
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Enhanced SPH Turbulence Modeling via Adaptive Kernel Correction & Multi-Scale Data Assimilation
🔗Tailscale
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Temporal Prompting Matters: Rethinking Referring Video Object Segmentation
📊Learned Metrics
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Inferring trust in recommendation systems from brain, behavioural, and physiological data
arxiv.org·1h
🔍Vector Forensics
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Will Developers Survive AI Takeover? Part 3: What Happens If You Stay Old School?
🧲RISC-V Archaeology
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RF-DETR Under the Hood: The Insights of a Real-Time Transformer Detection
towardsdatascience.com·2d
📊Quantization
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A mathematical certification for positivity conditions in Neural Networks with applications to partial monotonicity and Trustworthy AI
arxiv.org·3d
🧠Machine Learning
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All You Need for Object Detection: From Pixels, Points, and Prompts to Next-Gen Fusion and Multimodal LLMs/VLMs in Autonomous Vehicles
arxiv.org·3d
🤖Advanced OCR
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SwarmSys: Decentralized Swarm-Inspired Agents for Scalable and AdaptiveReasoning
🔲Cellular Automata
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Automated Peptide-Mimetic Design via Constraint-Based Generative Networks
🔍Vector Forensics
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Linking Heterogeneous Data with Coordinated Agent Flows for Social Media Analysis
arxiv.org·3d
📥Feed Aggregation
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PhysMaster: Mastering Physical Representation for Video Generation viaReinforcement Learning
📟Terminal Physics
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Clone Deterministic 3D Worlds with Geometrically-Regularized World Models
arxiv.org·3d
🌀Differential Geometry
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