Fahim Farook
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885I'm currently working on my second novel which is complete, but is in the edit stage. I wrote my first novel over 20 years ago but then didn't write much till now.
I post about #Coding, #Flutter, #Writing, #Movies and #TV. I'll also talk about #Technology, #Gadgets, #MachineLearning, #DeepLearning and a few other things as the fancy strikes ...
Lived in: ๐ฑ๐ฐ๐ธ๐ฆ๐บ๐ธ๐ณ๐ฟ๐ธ๐ฌ๐ฒ๐พ๐ฆ๐ช๐ซ๐ท๐ช๐ธ๐ต๐น๐ถ๐ฆ๐จ๐ฆ
Fahim Farook
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๐ฟ๐๐๐๐๐๐๐๐ฟ๐๐๐โ
Triflingtree@home.social
Telephone designed by Leonardo Da Vinci
Midjourney 4 AI Art
#stablediffusion #dalle2 #dalle #aiart #nightcafe #midjourney
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Fahim Farook
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RobDoesWords in January 2023 (looooooong)
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@Miteroni Wow! Thatโs a lot for a month you took off writing ๐ Unless of course, you didnโt write the stuff you published in January โฆ in that case, my bad.
You should do this kind of thing more often since I had no idea you had all this stuff there for reading. Going to go bookmark them so that I can read over the weekend. Or maybe have a pinned post on your profile with ongoing stuff youโre writing and perhaps a brief summary so that people know what youโre writing right now?
Itโs the descriptions you had above which piqued my curiosity โ hence the suggestion of a summary in a pinned post ๐
You should do this kind of thing more often since I had no idea you had all this stuff there for reading. Going to go bookmark them so that I can read over the weekend. Or maybe have a pinned post on your profile with ongoing stuff youโre writing and perhaps a brief summary so that people know what youโre writing right now?
Itโs the descriptions you had above which piqued my curiosity โ hence the suggestion of a summary in a pinned post ๐
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Fahim Farook
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Kenneth Tucker
kennethtucker@mastodon.cloud
Edited 3 years ago
test
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Snowy egret #bird #birds #birdphotography #photography
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Fahim Farook
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Fahim Farook
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Looks as if there were more interesting papers today to talk about ๐ A total of 17 papers posted out of a total of 89 new and updated papers in the cs.CV category today.
#AI #CV #NewPapers #DeepLearning #MachineLearning
#AI #CV #NewPapers #DeepLearning #MachineLearning
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Fahim Farook
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"DAG: Depth-Aware Guidance with Denoising Diffusion Probabilistic Models. (arXiv:2212.08861v2 [cs.CV] UPDATED)" โ A guidance method for diffusion models that uses estimated depth information derived from the rich intermediate representations of diffusion models.
Paper: http://arxiv.org/abs/2212.08861
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Qualitative comparisons of syntโฆ
Paper: http://arxiv.org/abs/2212.08861
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Qualitative comparisons of syntโฆ
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Fahim Farook
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"Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis. (arXiv:2212.05032v2 [cs.CV] UPDATED)" โ Improving the compositional skills of text-to-image models; specifically, obtainining more accurate attribute binding and better image compositions by incorporating linguistic structures with the diffusion guidance process based on the controllable properties of manipulating cross-attention layers in diffusion-based models.
Paper: http://arxiv.org/abs/2212.05032
Code: https://github.com/weixi-feng/structured-diffusion-guidance
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Three challenging phenomena in โฆ
Paper: http://arxiv.org/abs/2212.05032
Code: https://github.com/weixi-feng/structured-diffusion-guidance
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Three challenging phenomena in โฆ
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Fahim Farook
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"Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models. (arXiv:2211.17091v2 [cs.CV] UPDATED)" โ A generative SDE with score adjustment using an auxiliary discriminator with the goal of improving the original generative process of a pre-trained diffusion model by estimating the gap between the pre-trained score estimation and the true data score.
Paper: http://arxiv.org/abs/2211.17091
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Comparison of the denoising proโฆ
Paper: http://arxiv.org/abs/2211.17091
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Comparison of the denoising proโฆ
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Fahim Farook
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"Learning on tree architectures outperforms a convolutional feedforward network. (arXiv:2211.11378v3 [cs.CV] UPDATED)" โ A 3-layer tree architecture inspired by experimental-based dendritic tree adaptations is developed and applied to the offline and online learning of the CIFAR-10 database to show that this architecture outperforms the achievable success rates of the 5-layer convolutional LeNet.
Paper: http://arxiv.org/abs/2211.11378
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Comparison of offline and onlinโฆ
Paper: http://arxiv.org/abs/2211.11378
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Comparison of offline and onlinโฆ
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Fahim Farook
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"Continual Learning by Modeling Intra-Class Variation. (arXiv:2210.05398v2 [cs.LG] UPDATED)" โ An examination of memory-based continual learning which identifies that large variation in the representation space is crucial for avoiding catastrophic forgetting.
Paper: http://arxiv.org/abs/2210.05398
Code: https://github.com/yulonghui/moca
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Average intra-class angle deviaโฆ
Paper: http://arxiv.org/abs/2210.05398
Code: https://github.com/yulonghui/moca
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Average intra-class angle deviaโฆ
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Fahim Farook
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"Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions. (arXiv:2209.13603v3 [cs.CV] UPDATED)" โ A hybrid discrete-continuous (DISCO) group convolution for spherical convolutional neural networks (CNN) that is simultaneously equivariant and computationally scalable to high-resolution.
Paper: http://arxiv.org/abs/2209.13603
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Spherical CNN categorization
Paper: http://arxiv.org/abs/2209.13603
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Spherical CNN categorization
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Fahim Farook
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"Multi-Level Visual Similarity Based Personalized Tourist Attraction Recommendation Using Geo-Tagged Photos. (arXiv:2109.08275v2 [cs.MM] UPDATED)" โ A geo-tagged photo based tourist attraction recommendation system which utilizes the visual contents of photos and interaction behavior data to obtain the final embeddings of users and tourist attractions, which are then used to predict the visit probabilities.
Paper: http://arxiv.org/abs/2109.08275
Code: https://github.com/revaludo/MEAL
#AI #CV #NewPaper #DeepLearning #MachineLearning
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An illustration of the multi-leโฆ
Paper: http://arxiv.org/abs/2109.08275
Code: https://github.com/revaludo/MEAL
#AI #CV #NewPaper #DeepLearning #MachineLearning
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An illustration of the multi-leโฆ
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Fahim Farook
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"BiAdam: Fast Adaptive Bilevel Optimization Methods. (arXiv:2106.11396v3 [math.OC] UPDATED)" โ A novel fast adaptive bilevel framework to solve stochastic bilevel optimization problems that the outer problem is possibly nonconvex and the inner problem is strongly convex.
Paper: http://arxiv.org/abs/2106.11396
#AI #CV #NewPaper #DeepLearning #MachineLearning
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The basic idea of the convergenโฆ
Paper: http://arxiv.org/abs/2106.11396
#AI #CV #NewPaper #DeepLearning #MachineLearning
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The basic idea of the convergenโฆ
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Fahim Farook
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"Sparse Oblique Decision Trees: A Tool to Understand and Manipulate Neural Net Features. (arXiv:2104.02922v2 [cs.LG] UPDATED)" โ An effort to understanding which of the internal features computed by the neural net are responsible for a particular class, by mimicking part of the neural net with an oblique decision tree having sparse weight vectors at the decision nodes.
Paper: http://arxiv.org/abs/2104.02922
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Mimicking part of a neural net โฆ
Paper: http://arxiv.org/abs/2104.02922
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Mimicking part of a neural net โฆ
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Fahim Farook
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"Don't Play Favorites: Minority Guidance for Diffusion Models. (arXiv:2301.12334v1 [cs.LG])" โ A framework that can make the generation process of the diffusion models focus on the minority samples, which are instances that lie on low-density regions of a data manifold.
Paper: http://arxiv.org/abs/2301.12334
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Diffusion models play favoritesโฆ
Paper: http://arxiv.org/abs/2301.12334
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Diffusion models play favoritesโฆ
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Fahim Farook
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"SEGA: Instructing Diffusion using Semantic Dimensions. (arXiv:2301.12247v1 [cs.CV])" โ A semantic guidance method for diffusion models to allow making subtle and extensive edits and changes in composition and style, as well as optimize the overall artistic conception.
Paper: http://arxiv.org/abs/2301.12247
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Semantic control over image genโฆ
Paper: http://arxiv.org/abs/2301.12247
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Semantic control over image genโฆ
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Fahim Farook
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"Anticipate, Ensemble and Prune: Improving Convolutional Neural Networks via Aggregated Early Exits. (arXiv:2301.12168v1 [cs.LG])" โ A new training technique based on weighted ensembles of early exits, which aims at exploiting the information in the structure of networks to maximise their performance.
Paper: http://arxiv.org/abs/2301.12168
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Outline of the AEP technique. Oโฆ
Paper: http://arxiv.org/abs/2301.12168
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Outline of the AEP technique. Oโฆ
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@AngelaPreston Thank you ๐ My trouble usually is that once I start thinking about writing, the characters start taking over and I get so many scenes playing out in my head that thereโs no way to turn it off โฆ I wish they had a brain - computer interface so that I can just sit there and let the computer transcribe everything but alas, I guess Iโll just have to type it all out myself ๐
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Fahim Farook
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"ClusterFuG: Clustering Fully connected Graphs by Multicut. (arXiv:2301.12159v1 [cs.CV])" โ A simpler and potentially better performing graph clustering formulation based on multicut (a.k.a. weighted correlation clustering) on the complete graph.
Paper: http://arxiv.org/abs/2301.12159
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Example illustration of dense mโฆ
Paper: http://arxiv.org/abs/2301.12159
#AI #CV #NewPaper #DeepLearning #MachineLearning
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Example illustration of dense mโฆ
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