DavidVivancos/NeuraxonLife2-1M
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David Vivancos
DavidVivancos
AI & ML interests
Machine Learning, Deep Learning, NeuroTechnologies, Humanoid Robotics, Building https://artificiology.com Researching E-AGI
Recent Activity
updated
a dataset
about 3 hours ago
DavidVivancos/NeuraxonLife2-1M
posted
an
update
4 days ago
Need a new challenging Dataset? Now that #NeurIPS2025 is almost over.
https://huggingface.co/datasets/DavidVivancos/NeuraxonLife2-1M
1 Million #Neuraxon Artificial Lives, from almost 10000 Research Game runs, with more than 21 Million Neurons and almost 4 years of Simulated Life.
Read the preprint here https://www.researchgate.net/publication/397331336_Neuraxon
And here you have all the code: https://github.com/DavidVivancos/Neuraxon
published
a dataset
4 days ago
DavidVivancos/NeuraxonLife2-1M
Organizations
updated
a
dataset
about 3 hours ago
posted
an
update
4 days ago
Post
217
Need a new challenging Dataset? Now that #NeurIPS2025 is almost over.
DavidVivancos/NeuraxonLife2-1M
1 Million #Neuraxon Artificial Lives, from almost 10000 Research Game runs, with more than 21 Million Neurons and almost 4 years of Simulated Life.
Read the preprint here https://www.researchgate.net/publication/397331336_Neuraxon
And here you have all the code: https://github.com/DavidVivancos/Neuraxon
DavidVivancos/NeuraxonLife2-1M
1 Million #Neuraxon Artificial Lives, from almost 10000 Research Game runs, with more than 21 Million Neurons and almost 4 years of Simulated Life.
Read the preprint here https://www.researchgate.net/publication/397331336_Neuraxon
And here you have all the code: https://github.com/DavidVivancos/Neuraxon
published
a
dataset
4 days ago
updated
a
Space
8 days ago
posted
an
update
23 days ago
Post
295
Hi all!,
Neuraxon Game of Life is also live in demo at HuggingFace
DavidVivancos/NeuraxonLife
Preprint Paper: https://www.researchgate.net/publication/397331336_Neuraxon
Source Code of the Research verision: https://github.com/DavidVivancos/Neuraxon
HuggingFace Models are in the oven!
Hope you like it!
@DavidVivancos
Neuraxon Game of Life is also live in demo at HuggingFace
DavidVivancos/NeuraxonLife
Preprint Paper: https://www.researchgate.net/publication/397331336_Neuraxon
Source Code of the Research verision: https://github.com/DavidVivancos/Neuraxon
HuggingFace Models are in the oven!
Hope you like it!
@DavidVivancos
published
a
Space
23 days ago
updated
a
Space
23 days ago
posted
an
update
about 1 month ago
Post
973
Hi all!,
Neuraxon ( a novel Neural Growth & Computation Blueprint) is live in demo at HuggingFace DavidVivancos/Neuraxon
Paper: https://www.researchgate.net/publication/397331336_Neuraxon (on its way to arxiv too)
Code: https://github.com/DavidVivancos/Neuraxon
HuggingFace Model in the oven!
Hope you like it!
@DavidVivancos
Neuraxon ( a novel Neural Growth & Computation Blueprint) is live in demo at HuggingFace DavidVivancos/Neuraxon
Paper: https://www.researchgate.net/publication/397331336_Neuraxon (on its way to arxiv too)
Code: https://github.com/DavidVivancos/Neuraxon
HuggingFace Model in the oven!
Hope you like it!
@DavidVivancos
- 2 replies
published
a
Space
about 1 month ago
updated
a
Space
7 months ago
upvoted
a
paper
7 months ago
reacted to
dylanebert's
post with 👀
about 1 year ago
Post
2920
Keep track of the latest 3D releases with this space👉
dylanebert/research-tracker
- 2 replies
posted
an
update
over 1 year ago
Post
1985
#ICLM 2024 is almost there 🔥🔥🔥 PM if you will be in Vienna next week, Glad to catchup with the Hugging Face community there!
I would like to contribute 🎁 by releasing the sixth Knowledge Vault, with 100 lectures visualized from the last 10 years of ICML from 2014 to 2024, (10 from 2024 will be included after the conference) including knowledge graphs for all the Invited Lectures and some extras, with almost 3000 topics represented using AI.
You can explore it here:
🌏 https://theendofknowledge.com/Vaults/6/ICML-2015-2024.html
And you can learn more about the Vaults here:
📝https://www.linkedin.com/pulse/knowledge-vaults-david-vivancos-lbjef/
And previous Vaults relevant to the #huggingface community are:
🌏 [ @lexfridman 2018-2024 Interviews] https://theendofknowledge.com/Vaults/1/Lex100-2024.html
🌏 [ICLR 2014-2023] https://theendofknowledge.com/Vaults/2/ICLR2014-2023.html
🌏 [AIForGood 2017-2024] https://theendofknowledge.com/Vaults/4/AIForGood2017-2024.html
🌏 [CVPR 2015-2024] https://theendofknowledge.com/Vaults/5/CVPR-2015-2024.html
Hope you like them!
And great to see you all at #icml2024 @clem @thomwolf @julien-c and team
I would like to contribute 🎁 by releasing the sixth Knowledge Vault, with 100 lectures visualized from the last 10 years of ICML from 2014 to 2024, (10 from 2024 will be included after the conference) including knowledge graphs for all the Invited Lectures and some extras, with almost 3000 topics represented using AI.
You can explore it here:
🌏 https://theendofknowledge.com/Vaults/6/ICML-2015-2024.html
And you can learn more about the Vaults here:
📝https://www.linkedin.com/pulse/knowledge-vaults-david-vivancos-lbjef/
And previous Vaults relevant to the #huggingface community are:
🌏 [ @lexfridman 2018-2024 Interviews] https://theendofknowledge.com/Vaults/1/Lex100-2024.html
🌏 [ICLR 2014-2023] https://theendofknowledge.com/Vaults/2/ICLR2014-2023.html
🌏 [AIForGood 2017-2024] https://theendofknowledge.com/Vaults/4/AIForGood2017-2024.html
🌏 [CVPR 2015-2024] https://theendofknowledge.com/Vaults/5/CVPR-2015-2024.html
Hope you like them!
And great to see you all at #icml2024 @clem @thomwolf @julien-c and team
updated
a
dataset
over 1 year ago
Number of EEG Channels
2
#3 opened over 1 year ago
by
Shuohan
Has anyone been able to get a good accuracy on the dataset ?
👍
2
7
#1 opened over 2 years ago
by
dushyant007
posted
an
update
over 1 year ago
Post
2156
#ICLR 2024 is almost there 🔥🔥🔥 counting the days to be again in the beautiful city of Vienna participating in the The Twelfth International Conference on Learning Representations, hope to see many of the Hugging Face comunity there!
I would like to contribute 🎁 by releasing the second Knowledge Vault, with 100 lectures visualized from the last 10 years of ICLR from 2014 to 2023, including knowledge graphs for all the Invited Lectures and some extras, with almost 3000 topics represented. (Of course using several AI tools including Llama3)
You can explore it here:
🌏 https://theendofknowledge.com/Vaults/2/ICLR2014-2023.html
And you can learn more about the Vaults here:
📝https://www.linkedin.com/pulse/knowledge-vaults-david-vivancos-lbjef/
Hope you like the Knowledge Vault!
I would like to contribute 🎁 by releasing the second Knowledge Vault, with 100 lectures visualized from the last 10 years of ICLR from 2014 to 2023, including knowledge graphs for all the Invited Lectures and some extras, with almost 3000 topics represented. (Of course using several AI tools including Llama3)
You can explore it here:
🌏 https://theendofknowledge.com/Vaults/2/ICLR2014-2023.html
And you can learn more about the Vaults here:
📝https://www.linkedin.com/pulse/knowledge-vaults-david-vivancos-lbjef/
Hope you like the Knowledge Vault!
reacted to
akhaliq's
post with ❤️
almost 2 years ago
Post
Design2Code
How Far Are We From Automating Front-End Engineering?
Design2Code: How Far Are We From Automating Front-End Engineering? (2403.03163)
Generative AI has made rapid advancements in recent years, achieving unprecedented capabilities in multimodal understanding and code generation. This can enable a new paradigm of front-end development, in which multimodal LLMs might directly convert visual designs into code implementations. In this work, we formalize this as a Design2Code task and conduct comprehensive benchmarking. Specifically, we manually curate a benchmark of 484 diverse real-world webpages as test cases and develop a set of automatic evaluation metrics to assess how well current multimodal LLMs can generate the code implementations that directly render into the given reference webpages, given the screenshots as input. We also complement automatic metrics with comprehensive human evaluations. We develop a suite of multimodal prompting methods and show their effectiveness on GPT-4V and Gemini Pro Vision. We further finetune an open-source Design2Code-18B model that successfully matches the performance of Gemini Pro Vision. Both human evaluation and automatic metrics show that GPT-4V performs the best on this task compared to other models. Moreover, annotators think GPT-4V generated webpages can replace the original reference webpages in 49% of cases in terms of visual appearance and content; and perhaps surprisingly, in 64% of cases GPT-4V generated webpages are considered better than the original reference webpages. Our fine-grained break-down metrics indicate that open-source models mostly lag in recalling visual elements from the input webpages and in generating correct layout designs, while aspects like text content and coloring can be drastically improved with proper finetuning.
How Far Are We From Automating Front-End Engineering?
Design2Code: How Far Are We From Automating Front-End Engineering? (2403.03163)
Generative AI has made rapid advancements in recent years, achieving unprecedented capabilities in multimodal understanding and code generation. This can enable a new paradigm of front-end development, in which multimodal LLMs might directly convert visual designs into code implementations. In this work, we formalize this as a Design2Code task and conduct comprehensive benchmarking. Specifically, we manually curate a benchmark of 484 diverse real-world webpages as test cases and develop a set of automatic evaluation metrics to assess how well current multimodal LLMs can generate the code implementations that directly render into the given reference webpages, given the screenshots as input. We also complement automatic metrics with comprehensive human evaluations. We develop a suite of multimodal prompting methods and show their effectiveness on GPT-4V and Gemini Pro Vision. We further finetune an open-source Design2Code-18B model that successfully matches the performance of Gemini Pro Vision. Both human evaluation and automatic metrics show that GPT-4V performs the best on this task compared to other models. Moreover, annotators think GPT-4V generated webpages can replace the original reference webpages in 49% of cases in terms of visual appearance and content; and perhaps surprisingly, in 64% of cases GPT-4V generated webpages are considered better than the original reference webpages. Our fine-grained break-down metrics indicate that open-source models mostly lag in recalling visual elements from the input webpages and in generating correct layout designs, while aspects like text content and coloring can be drastically improved with proper finetuning.
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- 4 replies
Interesting to test, just downloaded the model, still shows 0 downloads... https://huggingface.co/SALT-NLP/Design2Code-18B-v0
liked
a
model
almost 2 years ago
