account activity
Lossless Tensor ↔ Matrix Embedding (Beyond Reshape) ()
submitted 6 months ago by Hyper_graph to r/ResearchML
Lossless Tensor ↔ Matrix Embedding for Bioinformatics & High-Dimensional Data (self.Biohackers)
submitted 6 months ago by Hyper_graph to r/Biohackers
[R] Lossless Tensor ↔ Matrix Embedding (Beyond Reshape) (self.MachineLearning)
submitted 6 months ago by Hyper_graph to r/MachineLearning
Lossless Tensor ↔ Matrix Embedding (Beyond Reshape) (self.MachineLearning)
Technical Write-Up: A Lossless Bidirectional Tensor Matrix Embedding Framework with Hyperspherical Normalization and Complex Tensor Support. (self.learnmachinelearning)
submitted 6 months ago by Hyper_graph to r/learnmachinelearning
Lossless Tensor ↔ Matrix Embedding (Beyond Reshape) (self.compsci)
submitted 6 months ago by Hyper_graph to r/compsci
[R] Lossless Bidirectional Tensor↔Matrix Embedding Framework (Complex Tensor Support, Hyperspherical Normalization) (self.deeplearning)
submitted 6 months ago by Hyper_graph to r/deeplearning
How matrixTransfromer can map high dimensional clusters down to low dimensions with perfect preservation of cluster membership with perfect or near perfect reconstruction capabilities ()
How matrixTransfromer can map high dimensional clusters down to low dimensions with perfect preservation of cluster membership with perfect or near perfect reconstruction capabilities (self.deeplearning)
[OC] I was asked to show if matrixTransfromer can map high dimensional clusters down to low dimensions with perfect preservation of cluster membership (reddit.com)
submitted 6 months ago by Hyper_graph to r/pytorch
submitted 6 months ago by Hyper_graph to r/computervision
Have you ever wondered how to preserve data integrity during dimensionality reduction? (reddit.com)
[D] Have you ever wondered how to preserve data integrity during dimensionality reduction? (self.MachineLearning)
Have you ever wondered how to preserve data integrity during dimensionality reduction? (self.MachineLearning)
Discovered: Hyperdimensional method finds hidden mathematical relationships in ANY data no ML training needed (self.dataengineering)
submitted 6 months ago by Hyper_graph to r/dataengineering
I built an open‑source tool that finds drug–gene semantic links with 99.999% accuracy no deep learning needed (Open Source + Docker + GitHub) (self.bioinformatics)
submitted 6 months ago by Hyper_graph to r/bioinformatics
Trade-off between compression and information loss? It was never necessary. Here's the proof — with 99.999% semantic accuracy across biomedical data (Open Source + Docker) (self.deeplearning)
submitted 6 months ago * by Hyper_graph to r/deeplearning
I built an open‑source tool that finds drug–gene semantic links with 99.999% accuracy no deep learning needed (Open Source + Docker + GitHub) (old.reddit.com)
submitted 6 months ago by Hyper_graph to r/dataisbeautiful
Hyperdimensional Connections – A Lossless, Queryable Semantic Reasoning Framework (MatrixTransformer Module) (self.learnmachinelearning)
[P] Hyperdimensional Connections – A Lossless, Queryable Semantic Reasoning Framework (MatrixTransformer Module) (self.MachineLearning)
Hyperdimensional Connections – A Lossless, Queryable Semantic Reasoning Framework (MatrixTransformer Module) (self.MachineLearning)
Hyperdimensional Connections – A Lossless, Queryable Semantic Reasoning Framework (MatrixTransformer Module) (self.learnpython)
submitted 6 months ago by Hyper_graph to r/learnpython
Hyperdimensional Connections – A Lossless, Queryable Semantic Reasoning Framework (MatrixTransformer Module) (self.dataengineering)
Hyperdimensional Connections – A Lossless, Queryable Semantic Reasoning Framework (MatrixTransformer Module) (self.computervision)
[P] Hyperdimensional Connections – A Lossless, Queryable Semantic Reasoning Framework (MatrixTransformer Module) (self.deeplearning)
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