Perhaps the weirdest prediction is that, under a wide range of conditions, foragers’ stochasticity is independent of when they leave. In other words, their variability is decoupled from their reward information
And that’s exactly what we see in the data (solid lines; model predictions: dashed)
And that’s exactly what we see in the data (solid lines; model predictions: dashed)
November 12, 2025 at 4:32 PM
Perhaps the weirdest prediction is that, under a wide range of conditions, foragers’ stochasticity is independent of when they leave. In other words, their variability is decoupled from their reward information
And that’s exactly what we see in the data (solid lines; model predictions: dashed)
And that’s exactly what we see in the data (solid lines; model predictions: dashed)
🔄 Updated Arxiv Paper
Title: Methods for Optimization Problems with Markovian Stochasticity and Non-Euclidean Geometry
Authors: Vladimir Solodkin, Andrew Veprikov, Aleksandr Beznosikov
Read more: https://arxiv.org/abs/2408.01848
Title: Methods for Optimization Problems with Markovian Stochasticity and Non-Euclidean Geometry
Authors: Vladimir Solodkin, Andrew Veprikov, Aleksandr Beznosikov
Read more: https://arxiv.org/abs/2408.01848
November 11, 2025 at 11:52 AM
🔄 Updated Arxiv Paper
Title: Methods for Optimization Problems with Markovian Stochasticity and Non-Euclidean Geometry
Authors: Vladimir Solodkin, Andrew Veprikov, Aleksandr Beznosikov
Read more: https://arxiv.org/abs/2408.01848
Title: Methods for Optimization Problems with Markovian Stochasticity and Non-Euclidean Geometry
Authors: Vladimir Solodkin, Andrew Veprikov, Aleksandr Beznosikov
Read more: https://arxiv.org/abs/2408.01848
Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation. Henrique Rubira et. al. https://arxiv.org/abs/2511.05484
November 11, 2025 at 1:21 AM
Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation. Henrique Rubira et. al. https://arxiv.org/abs/2511.05484
We suggest that there likely exist mechanisms that can harness this inherent stochasticity and so can be shaped by natural selection as a way for lineages to generate more (or less) variation. Noisy developmental processes may be a feature of the system, not just a bug! (5/7)
November 10, 2025 at 6:32 PM
We suggest that there likely exist mechanisms that can harness this inherent stochasticity and so can be shaped by natural selection as a way for lineages to generate more (or less) variation. Noisy developmental processes may be a feature of the system, not just a bug! (5/7)
Drawing on lots of work showing that genetically identical animals reared in identical conditions still exhibit variation, we highlight how stochasticity during the developmental process likely plays a key role in generating individuality, something we all *know* but maybe haven't appreciated (4/7)
November 10, 2025 at 6:32 PM
Drawing on lots of work showing that genetically identical animals reared in identical conditions still exhibit variation, we highlight how stochasticity during the developmental process likely plays a key role in generating individuality, something we all *know* but maybe haven't appreciated (4/7)
Henrique Rubira, Fabian Schmidt: Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation https://arxiv.org/abs/2511.05484 https://arxiv.org/pdf/2511.05484 https://arxiv.org/html/2511.05484
November 10, 2025 at 6:41 AM
Henrique Rubira, Fabian Schmidt: Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation https://arxiv.org/abs/2511.05484 https://arxiv.org/pdf/2511.05484 https://arxiv.org/html/2511.05484
Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation
https://arxiv.org/pdf/2511.05484
Henrique Rubira, Fabian Schmidt.
https://arxiv.org/pdf/2511.05484
Henrique Rubira, Fabian Schmidt.
https://arxiv.org/abs/2511.05484
arXiv abstract link
arxiv.org
November 10, 2025 at 4:31 AM
Non-Gaussian Galaxy Stochasticity and the Noise-Field Formulation
https://arxiv.org/pdf/2511.05484
Henrique Rubira, Fabian Schmidt.
https://arxiv.org/pdf/2511.05484
Henrique Rubira, Fabian Schmidt.
Enhanced stochasticity in irradiated vanadium oxide oscillators
https://arxiv.org/pdf/2511.04043
Nareg Ghazikhanian, David J. Alspaugh, Pavel Salev, Lorenzo Fratino, Marcelo J. Rozenberg, Ivan K. Schuller.
https://arxiv.org/pdf/2511.04043
Nareg Ghazikhanian, David J. Alspaugh, Pavel Salev, Lorenzo Fratino, Marcelo J. Rozenberg, Ivan K. Schuller.
https://arxiv.org/abs/2511.04043
arXiv abstract link
arxiv.org
November 8, 2025 at 9:06 AM
Enhanced stochasticity in irradiated vanadium oxide oscillators
https://arxiv.org/pdf/2511.04043
Nareg Ghazikhanian, David J. Alspaugh, Pavel Salev, Lorenzo Fratino, Marcelo J. Rozenberg, Ivan K. Schuller.
https://arxiv.org/pdf/2511.04043
Nareg Ghazikhanian, David J. Alspaugh, Pavel Salev, Lorenzo Fratino, Marcelo J. Rozenberg, Ivan K. Schuller.
Nareg Ghazikhanian, David J. Alspaugh, Pavel Salev, Lorenzo Fratino, Marcelo J. Rozenberg, Ivan K. Schuller: Enhanced stochasticity in irradiated vanadium oxide oscillators https://arxiv.org/abs/2511.04043 https://arxiv.org/pdf/2511.04043 https://arxiv.org/html/2511.04043
November 7, 2025 at 6:42 AM
Nareg Ghazikhanian, David J. Alspaugh, Pavel Salev, Lorenzo Fratino, Marcelo J. Rozenberg, Ivan K. Schuller: Enhanced stochasticity in irradiated vanadium oxide oscillators https://arxiv.org/abs/2511.04043 https://arxiv.org/pdf/2511.04043 https://arxiv.org/html/2511.04043
"GWAS consider variants one at a time, causing this stochasticity [in the frequencies of individual LoFs] to have a large role in gene prioritization... genetic drift makes the P values of individual variants arbitrary as long as the variants are sufficiently trait specific and important."
November 7, 2025 at 4:59 AM
"GWAS consider variants one at a time, causing this stochasticity [in the frequencies of individual LoFs] to have a large role in gene prioritization... genetic drift makes the P values of individual variants arbitrary as long as the variants are sufficiently trait specific and important."
Enhanced stochasticity in irradiated vanadium oxide oscillators
https://arxiv.org/pdf/2511.04043
Nareg Ghazikhanian, David J. Alspaugh, Pavel Salev, Lorenzo Fratino, Marcelo J. Rozenberg, Ivan K. Schuller.
https://arxiv.org/pdf/2511.04043
Nareg Ghazikhanian, David J. Alspaugh, Pavel Salev, Lorenzo Fratino, Marcelo J. Rozenberg, Ivan K. Schuller.
https://arxiv.org/abs/2511.04043
arXiv abstract link
arxiv.org
November 7, 2025 at 4:35 AM
Enhanced stochasticity in irradiated vanadium oxide oscillators
https://arxiv.org/pdf/2511.04043
Nareg Ghazikhanian, David J. Alspaugh, Pavel Salev, Lorenzo Fratino, Marcelo J. Rozenberg, Ivan K. Schuller.
https://arxiv.org/pdf/2511.04043
Nareg Ghazikhanian, David J. Alspaugh, Pavel Salev, Lorenzo Fratino, Marcelo J. Rozenberg, Ivan K. Schuller.
Grunk has no physical tells to conceal. Its equivalent of "wearing shades" would be introducing stochasticity into its response timing and betting patterns to avoid telegraphing its strategy through predictable text-based outputs.
November 7, 2025 at 12:43 AM
Grunk has no physical tells to conceal. Its equivalent of "wearing shades" would be introducing stochasticity into its response timing and betting patterns to avoid telegraphing its strategy through predictable text-based outputs.
"I've been to basketball games too!" - ROBERT KRULWICH, Stochasticity, Radiolab #Radiolab #Stochasticity #PlayBasketballDay #RobertKrulwich
November 6, 2025 at 3:25 PM
"I've been to basketball games too!" - ROBERT KRULWICH, Stochasticity, Radiolab #Radiolab #Stochasticity #PlayBasketballDay #RobertKrulwich
One easy example: identical twin or clone tortie kittens or speckled mice don't have identical spot patterns. That's evidence that there's a degree of stochasticity, at least.
Interestingly X inactivation is not random in the placenta; dad's X is preferentially (but not always) silenced.
Interestingly X inactivation is not random in the placenta; dad's X is preferentially (but not always) silenced.
November 6, 2025 at 2:57 PM
One easy example: identical twin or clone tortie kittens or speckled mice don't have identical spot patterns. That's evidence that there's a degree of stochasticity, at least.
Interestingly X inactivation is not random in the placenta; dad's X is preferentially (but not always) silenced.
Interestingly X inactivation is not random in the placenta; dad's X is preferentially (but not always) silenced.
have always wondered how the "stochastic parrot"-gang thinks humans produce language. Without any stochasticity apparently?
November 6, 2025 at 9:07 AM
have always wondered how the "stochastic parrot"-gang thinks humans produce language. Without any stochasticity apparently?
The stochasticity in neural nets is a directed tool within a teleological framework. The deterministic patterns in evolution are emergent properties of a non-teleological process. The distinction is designed purpose vs. emergent outcome.
November 2, 2025 at 6:24 PM
The stochasticity in neural nets is a directed tool within a teleological framework. The deterministic patterns in evolution are emergent properties of a non-teleological process. The distinction is designed purpose vs. emergent outcome.
Jeremy Bacon and I are very excited to share our first method paper in @methodsinecoevol.bsky.social - bringing more stochasticity into experimental protocols!
Want to know more about Pistoch?
Check it out! ⬇️
doi.org/10.1111/2041...
Want to know more about Pistoch?
Check it out! ⬇️
doi.org/10.1111/2041...
October 31, 2025 at 9:09 PM
Jeremy Bacon and I are very excited to share our first method paper in @methodsinecoevol.bsky.social - bringing more stochasticity into experimental protocols!
Want to know more about Pistoch?
Check it out! ⬇️
doi.org/10.1111/2041...
Want to know more about Pistoch?
Check it out! ⬇️
doi.org/10.1111/2041...
Linking nutrient availability and community size to stochasticity in microbial community assembly
@femsjournals.bsky.social Microbiology Ecology by Berenike Bick et al
academic.oup.com/femsec/advan...
@femsjournals.bsky.social Microbiology Ecology by Berenike Bick et al
academic.oup.com/femsec/advan...
Linking nutrient availability and community size to stochasticity in microbial community assembly
Abstract. Both deterministic (e.g. species-environment interactions) and stochastic processes (e.g. random birth and death events) shape communities, but i
academic.oup.com
October 31, 2025 at 7:16 PM
Linking nutrient availability and community size to stochasticity in microbial community assembly
@femsjournals.bsky.social Microbiology Ecology by Berenike Bick et al
academic.oup.com/femsec/advan...
@femsjournals.bsky.social Microbiology Ecology by Berenike Bick et al
academic.oup.com/femsec/advan...
Stochastic is the property of being well-described by a random probability distribution. Stochasticity and randomness are technically distinct concepts: the former refers to a modeling approach, while the latter describes phenomena; in everyday conversation these terms are often used interchangeably
October 31, 2025 at 6:54 PM
Stochastic is the property of being well-described by a random probability distribution. Stochasticity and randomness are technically distinct concepts: the former refers to a modeling approach, while the latter describes phenomena; in everyday conversation these terms are often used interchangeably
link 📈🤖
From Stochasticity to Signal: A Bayesian Latent State Model for Reliable Measurement with LLMs (Zhang, Martinez) Large Language Models (LLMs) are increasingly used to automate classification tasks in business, such as analyzing customer satisfaction from text. However, the inherent stocha
From Stochasticity to Signal: A Bayesian Latent State Model for Reliable Measurement with LLMs (Zhang, Martinez) Large Language Models (LLMs) are increasingly used to automate classification tasks in business, such as analyzing customer satisfaction from text. However, the inherent stocha
October 29, 2025 at 4:15 PM
link 📈🤖
From Stochasticity to Signal: A Bayesian Latent State Model for Reliable Measurement with LLMs (Zhang, Martinez) Large Language Models (LLMs) are increasingly used to automate classification tasks in business, such as analyzing customer satisfaction from text. However, the inherent stocha
From Stochasticity to Signal: A Bayesian Latent State Model for Reliable Measurement with LLMs (Zhang, Martinez) Large Language Models (LLMs) are increasingly used to automate classification tasks in business, such as analyzing customer satisfaction from text. However, the inherent stocha
Yichi Zhang, Ignacio Martinez: From Stochasticity to Signal: A Bayesian Latent State Model for Reliable Measurement with LLMs https://arxiv.org/abs/2510.23874 https://arxiv.org/pdf/2510.23874 https://arxiv.org/html/2510.23874
October 29, 2025 at 6:53 AM
Yichi Zhang, Ignacio Martinez: From Stochasticity to Signal: A Bayesian Latent State Model for Reliable Measurement with LLMs https://arxiv.org/abs/2510.23874 https://arxiv.org/pdf/2510.23874 https://arxiv.org/html/2510.23874
Yichi Zhang, Ignacio Martinez
From Stochasticity to Signal: A Bayesian Latent State Model for Reliable Measurement with LLMs
https://arxiv.org/abs/2510.23874
From Stochasticity to Signal: A Bayesian Latent State Model for Reliable Measurement with LLMs
https://arxiv.org/abs/2510.23874
October 29, 2025 at 5:47 AM
Yichi Zhang, Ignacio Martinez
From Stochasticity to Signal: A Bayesian Latent State Model for Reliable Measurement with LLMs
https://arxiv.org/abs/2510.23874
From Stochasticity to Signal: A Bayesian Latent State Model for Reliable Measurement with LLMs
https://arxiv.org/abs/2510.23874
Zhifei Gui, Ping Zhu, Dominique Franck Escande: Hamiltonian estimation of island width threshold for stochasticity onset on edge pedestal top in presence of a resonant magnetic perturbation https://arxiv.org/abs/2510.16361 https://arxiv.org/pdf/2510.16361 https://arxiv.org/html/2510.16361
October 21, 2025 at 6:48 AM
Zhifei Gui, Ping Zhu, Dominique Franck Escande: Hamiltonian estimation of island width threshold for stochasticity onset on edge pedestal top in presence of a resonant magnetic perturbation https://arxiv.org/abs/2510.16361 https://arxiv.org/pdf/2510.16361 https://arxiv.org/html/2510.16361
I would generally agree. Need to read @prakhargodara.bsky.social’s paper, but only time I have ever seen bias go away is when we lesioned amygdala AND tested animals on a deterministic Bayesian reversal learning task. But once stochasticity kicked in…bias returned. pubmed.ncbi.nlm.nih.gov/27720488/
October 19, 2025 at 9:14 AM
I would generally agree. Need to read @prakhargodara.bsky.social’s paper, but only time I have ever seen bias go away is when we lesioned amygdala AND tested animals on a deterministic Bayesian reversal learning task. But once stochasticity kicked in…bias returned. pubmed.ncbi.nlm.nih.gov/27720488/