Flowing Backwards: Improving Normalizing Flows via Reverse Representation Alignment
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2511.22345
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Published
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12
AI & ML interests
Computer Vision Technology and Data Collection for Anime Waifu
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wangsssssss
authored
a
paper
6 days ago
AbstractPhil
posted
an
update
11 days ago
Post
315
Many updates. Cantor route experiments, GeoViT-david-beans 75% test standalone cifar100 geofractal 30m encoder. MultiHeaded Cantor Attention heavily optimized. The migration is primarily complete between geofractal and geovocab2.
https://github.com/AbstractEyes/geofractal/blob/main/src/geofractal/model/david_beans/model.py
Cantor route staircase and wormhole excavation findings posted. A full article will be posted to represent the findings of cantor routing and the potentials for self-learning fractals through loss.
https://github.com/AbstractEyes/lattice_vocabulary/blob/master/src/geovocab2/proofs/cantor_steps_experiments.md
The steps experiments show profoundly important implications for cross-contamination problems with fractal and linear spaces, with some currently assessed as useful utilities as of today.
Today the classification experiment will continue by using mini-experts applied to patches within a miniature david-beans. The mini-experts were an accident that showed improvement to the fidelity and not destruction, so those experiments are to be continued. geovit-david-beans trainer was added to the first repo.
https://github.com/AbstractEyes/geofractal/blob/main/src/geofractal/model/david_beans/model.py
Cantor route staircase and wormhole excavation findings posted. A full article will be posted to represent the findings of cantor routing and the potentials for self-learning fractals through loss.
https://github.com/AbstractEyes/lattice_vocabulary/blob/master/src/geovocab2/proofs/cantor_steps_experiments.md
The steps experiments show profoundly important implications for cross-contamination problems with fractal and linear spaces, with some currently assessed as useful utilities as of today.
Today the classification experiment will continue by using mini-experts applied to patches within a miniature david-beans. The mini-experts were an accident that showed improvement to the fidelity and not destruction, so those experiments are to be continued. geovit-david-beans trainer was added to the first repo.
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- 1 reply
wangsssssss
authored
a
paper
15 days ago
AbstractPhil
posted
an
update
15 days ago
Post
290
For those using my geovocab2 repo for SimplexFactory, CantorRouteFactory, fusion modulations, model code import, training weights and models, or specific extraction systems; I will be refactoring in the coming days.
The new repo for all geometric, cantor, and fractal-based trainings will be;
https://github.com/AbstractEyes/geofractal
The change is due to MY own excessive abuse of the vocabulary repo and the excessive overuse of subfolders attached to a working pycharm project. These behaviors should be decoupled and I apologize for making such code bloat through experimentation.
Directly installing the geofractal repo will install geovocab2 as a sidecar. However, there will be a clause within the geovocab2 to warn the user.
You have my deepest and most sincere apologies for breaking your active working code if I do. I know this is difficult work so please bare with my efforts as I progress the codebase to it's next state of truth vs experimentation.
Please, reach out to me directly if you have problems converting.
It is meant to be a DIRECT and UTILIZABLE pain-free conversion that will enable the same interface from both geovocab2 and all future updated model code changes applied to geofractal - once the geofractal module is imported.
The original goevocab2 will contain outdated train code instead of full deprecation with a direct warning - and the geovocab2 repo will be folding in geovocab and geovocab2 into matching aliased systems - allowing the factory and extraction structure to behave within geovocab2 and training to behave within geofractal by design.
I will be introducing a direct alias system that will hopefully allow a smooth transition system to the new codebase, but there's never a way to account for those you don't know are using your work. This will include pyi files for the aliases and some necessary elemental additions that may break current functionality in systems I'm unaware of. Please reach out if I break something crucial that you require.
The new repo for all geometric, cantor, and fractal-based trainings will be;
https://github.com/AbstractEyes/geofractal
The change is due to MY own excessive abuse of the vocabulary repo and the excessive overuse of subfolders attached to a working pycharm project. These behaviors should be decoupled and I apologize for making such code bloat through experimentation.
Directly installing the geofractal repo will install geovocab2 as a sidecar. However, there will be a clause within the geovocab2 to warn the user.
You have my deepest and most sincere apologies for breaking your active working code if I do. I know this is difficult work so please bare with my efforts as I progress the codebase to it's next state of truth vs experimentation.
Please, reach out to me directly if you have problems converting.
It is meant to be a DIRECT and UTILIZABLE pain-free conversion that will enable the same interface from both geovocab2 and all future updated model code changes applied to geofractal - once the geofractal module is imported.
The original goevocab2 will contain outdated train code instead of full deprecation with a direct warning - and the geovocab2 repo will be folding in geovocab and geovocab2 into matching aliased systems - allowing the factory and extraction structure to behave within geovocab2 and training to behave within geofractal by design.
I will be introducing a direct alias system that will hopefully allow a smooth transition system to the new codebase, but there's never a way to account for those you don't know are using your work. This will include pyi files for the aliases and some necessary elemental additions that may break current functionality in systems I'm unaware of. Please reach out if I break something crucial that you require.
narugo1992
updated
9
datasets
23 days ago
deepghs/csip_eval
Preview
•
Updated
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29
deepghs/csip_v1
Preview
•
Updated
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73
deepghs/csip
Updated
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158
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1
deepghs/nsfw_detect
Preview
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Updated
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374
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57
deepghs/tagger_vocabs
Preview
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Updated
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118
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1
deepghs/anime_blurry_preparation
Updated
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33
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3
deepghs/anime_halfbody_detection
Updated
•
47
deepghs/anime_eye_detection
Updated
•
36
deepghs/anime_dbrating
Preview
•
Updated
•
44
AbstractPhil
posted
an
update
23 days ago
Post
305
Lyra, Lune, Cantor, k-simplex, and many relational experiments.
AbstractPhil/sd15-flow-matching-lune
Today I will be updating the space to support all three forms of lyra to enable tinkertoying with various other models like flux-schnell and sdxl.
It should be noted, I didn't know nvidia actually released a model named LYRA. This model has no association with NVIDIA's LYRA model. This LYRA is full MIT licensed. If necessary I'll rename this model, but I don't think it'll matter.
Unlike NORMAL VAE, this VAE was intentionally meant to introduce incorrectness into the correctness that already exists. The concept was to pull towards a goal - t5-xl being the primary goal.
AbstractPhil/vae-lyra Lyra is a multimodal MM-VAE prototype meant to encompass a fusion of multiple types of encodings together. Tested with circle of fifths audio and text, multiple text encoders, vision and text encoder, and a few other smaller prototypes that yielded.
Lyra has a few direct clip_l and t5_xl prototypes that directly learned to associate clip_l with t5-base. This version worked, so version 2 expanded the concept.
AbstractPhil/vae-lyra-sdxl-t5xl is another prototype using CLIP_L and CLIP_G fused with T5_XL for the first version, directly utilizing projection with minimal geometric and cantor assistance. The shared layers ended up teaching CLIP_L how to be CLIP_G and the output ended up warping too much for SDXL or SD15 to understand.
AbstractPhil/vae-lyra-xl-adaptive-cantor
Utilizing adapative cantor is the successful prototype where CLIP_L and CLIP_G learned independent structures internally, where CLIP_L and T5_XL learned a route with CLIP_G and T5_XL in parallel conjunction. This enabled two entirely divergent opinions, and thus enables the t5-xl to manipulate either the clip_l or the clip_g for models like FLUX-SCHNELL or SDXL.
Each lyra has a purpose, and each purpose matters.
AbstractPhil/sd15-flow-matching-lune
Today I will be updating the space to support all three forms of lyra to enable tinkertoying with various other models like flux-schnell and sdxl.
It should be noted, I didn't know nvidia actually released a model named LYRA. This model has no association with NVIDIA's LYRA model. This LYRA is full MIT licensed. If necessary I'll rename this model, but I don't think it'll matter.
Unlike NORMAL VAE, this VAE was intentionally meant to introduce incorrectness into the correctness that already exists. The concept was to pull towards a goal - t5-xl being the primary goal.
AbstractPhil/vae-lyra Lyra is a multimodal MM-VAE prototype meant to encompass a fusion of multiple types of encodings together. Tested with circle of fifths audio and text, multiple text encoders, vision and text encoder, and a few other smaller prototypes that yielded.
Lyra has a few direct clip_l and t5_xl prototypes that directly learned to associate clip_l with t5-base. This version worked, so version 2 expanded the concept.
AbstractPhil/vae-lyra-sdxl-t5xl is another prototype using CLIP_L and CLIP_G fused with T5_XL for the first version, directly utilizing projection with minimal geometric and cantor assistance. The shared layers ended up teaching CLIP_L how to be CLIP_G and the output ended up warping too much for SDXL or SD15 to understand.
AbstractPhil/vae-lyra-xl-adaptive-cantor
Utilizing adapative cantor is the successful prototype where CLIP_L and CLIP_G learned independent structures internally, where CLIP_L and T5_XL learned a route with CLIP_G and T5_XL in parallel conjunction. This enabled two entirely divergent opinions, and thus enables the t5-xl to manipulate either the clip_l or the clip_g for models like FLUX-SCHNELL or SDXL.
Each lyra has a purpose, and each purpose matters.
narugo1992
updated
4
datasets
23 days ago
narugo1992
updated
2
models
23 days ago