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#invariance — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #invariance, aggregated by home.social.

  1. I really enjoy reading the expanding literature on #invariance of #ValueSets. Two interesting papers and a taxonomy regarding #obsolescence

    1- link.springer.com/article/10.1

    2- sciencedirect.com/science/arti

    3- link.springer.com/article/10.1

    "As time and methods advance, the bedrock of applied valuation research naturally becomes increasingly unreliable, and, as a field, we need to consider how to approach this challenge."

    #HealthEconomics
    #EQ5D #Psychometrics

  2. I really enjoy reading the expanding literature on #invariance of #ValueSets. Two interesting papers and a taxonomy regarding #obsolescence

    1- link.springer.com/article/10.1

    2- sciencedirect.com/science/arti

    3- link.springer.com/article/10.1

    "As time and methods advance, the bedrock of applied valuation research naturally becomes increasingly unreliable, and, as a field, we need to consider how to approach this challenge."

    #HealthEconomics
    #EQ5D #Psychometrics

  3. I really enjoy reading the expanding literature on #invariance of #ValueSets. Two interesting papers and a taxonomy regarding #obsolescence

    1- link.springer.com/article/10.1

    2- sciencedirect.com/science/arti

    3- link.springer.com/article/10.1

    "As time and methods advance, the bedrock of applied valuation research naturally becomes increasingly unreliable, and, as a field, we need to consider how to approach this challenge."

    #HealthEconomics
    #EQ5D #Psychometrics

  4. I really enjoy reading the expanding literature on #invariance of #ValueSets. Two interesting papers and a taxonomy regarding #obsolescence

    1- link.springer.com/article/10.1

    2- sciencedirect.com/science/arti

    3- link.springer.com/article/10.1

    "As time and methods advance, the bedrock of applied valuation research naturally becomes increasingly unreliable, and, as a field, we need to consider how to approach this challenge."

    #HealthEconomics
    #EQ5D #Psychometrics

  5. 'Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces', by Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy.

    jmlr.org/papers/v25/23-0115.ht

    #gaussian #invariance #cov

  6. 'Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces', by Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy.

    jmlr.org/papers/v25/23-0115.ht

    #gaussian #invariance #cov

  7. 'Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces', by Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy.

    jmlr.org/papers/v25/23-0115.ht

    #gaussian #invariance #cov

  8. 'Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces', by Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy.

    jmlr.org/papers/v25/23-0115.ht

    #gaussian #invariance #cov

  9. 'Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces', by Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy.

    jmlr.org/papers/v25/23-0115.ht

    #gaussian #invariance #cov

  10. 'Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case', by Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy.

    jmlr.org/papers/v25/22-1434.ht

    #gaussian #invariance #spatiotemporal

  11. 'Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case', by Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy.

    jmlr.org/papers/v25/22-1434.ht

    #gaussian #invariance #spatiotemporal

  12. 'Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case', by Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy.

    jmlr.org/papers/v25/22-1434.ht

    #gaussian #invariance #spatiotemporal

  13. 'Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case', by Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy.

    jmlr.org/papers/v25/22-1434.ht

    #gaussian #invariance #spatiotemporal

  14. 'Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case', by Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy.

    jmlr.org/papers/v25/22-1434.ht

    #gaussian #invariance #spatiotemporal

  15. 'Effect-Invariant Mechanisms for Policy Generalization', by Sorawit Saengkyongam, Niklas Pfister, Predrag Klasnja, Susan Murphy, Jonas Peters.

    jmlr.org/papers/v25/23-0802.ht

    #causal #generalization #invariance

  16. 'Effect-Invariant Mechanisms for Policy Generalization', by Sorawit Saengkyongam, Niklas Pfister, Predrag Klasnja, Susan Murphy, Jonas Peters.

    jmlr.org/papers/v25/23-0802.ht

    #causal #generalization #invariance

  17. 'Effect-Invariant Mechanisms for Policy Generalization', by Sorawit Saengkyongam, Niklas Pfister, Predrag Klasnja, Susan Murphy, Jonas Peters.

    jmlr.org/papers/v25/23-0802.ht

    #causal #generalization #invariance

  18. 'Effect-Invariant Mechanisms for Policy Generalization', by Sorawit Saengkyongam, Niklas Pfister, Predrag Klasnja, Susan Murphy, Jonas Peters.

    jmlr.org/papers/v25/23-0802.ht

    #causal #generalization #invariance

  19. 'Effect-Invariant Mechanisms for Policy Generalization', by Sorawit Saengkyongam, Niklas Pfister, Predrag Klasnja, Susan Murphy, Jonas Peters.

    jmlr.org/papers/v25/23-0802.ht

    #causal #generalization #invariance

  20. Interpolation Can Provably Preclude Invariance arxiv.org/abs/2211.15724
    #Overfitting to the point of #interpolation can hinder invariance-inducing objectives: One cannot assume a #DeepLearninig model with an invariance penalty will indeed achieve any form of #invariance… suggests that “benign overfitting,” in which models generalize well despite interpolating, might not favorably extend to settings in which #robustness or #fairness are desirable.

  21. Interpolation Can Provably Preclude Invariance arxiv.org/abs/2211.15724
    #Overfitting to the point of #interpolation can hinder invariance-inducing objectives: One cannot assume a #DeepLearninig model with an invariance penalty will indeed achieve any form of #invariance… suggests that “benign overfitting,” in which models generalize well despite interpolating, might not favorably extend to settings in which #robustness or #fairness are desirable.

  22. Interpolation Can Provably Preclude Invariance arxiv.org/abs/2211.15724
    #Overfitting to the point of #interpolation can hinder invariance-inducing objectives: One cannot assume a #DeepLearninig model with an invariance penalty will indeed achieve any form of #invariance… suggests that “benign overfitting,” in which models generalize well despite interpolating, might not favorably extend to settings in which #robustness or #fairness are desirable.

  23. Interpolation Can Provably Preclude Invariance arxiv.org/abs/2211.15724
    #Overfitting to the point of #interpolation can hinder invariance-inducing objectives: One cannot assume a #DeepLearninig model with an invariance penalty will indeed achieve any form of #invariance… suggests that “benign overfitting,” in which models generalize well despite interpolating, might not favorably extend to settings in which #robustness or #fairness are desirable.

  24. Interpolation Can Provably Preclude Invariance arxiv.org/abs/2211.15724
    #Overfitting to the point of #interpolation can hinder invariance-inducing objectives: One cannot assume a #DeepLearninig model with an invariance penalty will indeed achieve any form of #invariance… suggests that “benign overfitting,” in which models generalize well despite interpolating, might not favorably extend to settings in which #robustness or #fairness are desirable.

  25. "By definition, only amodal properties (information not specific to a particular sensory system; e.g., tempo, rhythm, duration, intensity) can be redundantly specified across the senses."

    In other words, cross-modal redundancy is a type of invariance or symmetry with respect to transformation of sensory modality.

    ncbi.nlm.nih.gov/pmc/articles/

    🧵 More excerpts below 👇

    #Neuroscience #Psychology #Attention #Invariance #Symmetry

  26. "By definition, only amodal properties (information not specific to a particular sensory system; e.g., tempo, rhythm, duration, intensity) can be redundantly specified across the senses."

    In other words, cross-modal redundancy is a type of invariance or symmetry with respect to transformation of sensory modality.

    ncbi.nlm.nih.gov/pmc/articles/

    🧵 More excerpts below 👇

    #Neuroscience #Psychology #Attention #Invariance #Symmetry

  27. "By definition, only amodal properties (information not specific to a particular sensory system; e.g., tempo, rhythm, duration, intensity) can be redundantly specified across the senses."

    In other words, cross-modal redundancy is a type of invariance or symmetry with respect to transformation of sensory modality.

    ncbi.nlm.nih.gov/pmc/articles/

    🧵 More excerpts below 👇

    #Neuroscience #Psychology #Attention #Invariance #Symmetry

  28. "By definition, only amodal properties (information not specific to a particular sensory system; e.g., tempo, rhythm, duration, intensity) can be redundantly specified across the senses."

    In other words, cross-modal redundancy is a type of invariance or symmetry with respect to transformation of sensory modality.

    ncbi.nlm.nih.gov/pmc/articles/

    🧵 More excerpts below 👇

    #Neuroscience #Psychology #Attention #Invariance #Symmetry

  29. "By definition, only amodal properties (information not specific to a particular sensory system; e.g., tempo, rhythm, duration, intensity) can be redundantly specified across the senses."

    In other words, cross-modal redundancy is a type of invariance or symmetry with respect to transformation of sensory modality.

    ncbi.nlm.nih.gov/pmc/articles/

    🧵 More excerpts below 👇

    #Neuroscience #Psychology #Attention #Invariance #Symmetry

  30. @teixi

    All linguistic communication requires symbols, no?

    I like to think of metaphors as latent analogies. More on this here:

    yohanjohn.com/axispraxis/metap

    Both metaphor and analogy are in turn types of #symmetry or #invariance.

    3quarksdaily.com/3quarksdaily/

  31. @teixi

    All linguistic communication requires symbols, no?

    I like to think of metaphors as latent analogies. More on this here:

    yohanjohn.com/axispraxis/metap

    Both metaphor and analogy are in turn types of #symmetry or #invariance.

    3quarksdaily.com/3quarksdaily/

  32. @teixi

    All linguistic communication requires symbols, no?

    I like to think of metaphors as latent analogies. More on this here:

    yohanjohn.com/axispraxis/metap

    Both metaphor and analogy are in turn types of #symmetry or #invariance.

    3quarksdaily.com/3quarksdaily/

  33. @teixi

    All linguistic communication requires symbols, no?

    I like to think of metaphors as latent analogies. More on this here:

    yohanjohn.com/axispraxis/metap

    Both metaphor and analogy are in turn types of #symmetry or #invariance.

    3quarksdaily.com/3quarksdaily/

  34. #Introduction

    I'm a senior researcher at Microsoft Research Health futures in Amsterdam/Cambridge.

    My research interests include invariance/equivariance, causality and representation learning, especially the interplay of these 3 things. All applied to medical imaging.

    #machinelearning #deeplearning #causality #invariance

  35. #Introduction

    I'm a senior researcher at Microsoft Research Health futures in Amsterdam/Cambridge.

    My research interests include invariance/equivariance, causality and representation learning, especially the interplay of these 3 things. All applied to medical imaging.

    #machinelearning #deeplearning #causality #invariance

  36. #Introduction

    I'm a senior researcher at Microsoft Research Health futures in Amsterdam/Cambridge.

    My research interests include invariance/equivariance, causality and representation learning, especially the interplay of these 3 things. All applied to medical imaging.

    #machinelearning #deeplearning #causality #invariance

  37. #Introduction

    I'm a senior researcher at Microsoft Research Health futures in Amsterdam/Cambridge.

    My research interests include invariance/equivariance, causality and representation learning, especially the interplay of these 3 things. All applied to medical imaging.

    #machinelearning #deeplearning #causality #invariance

  38. Interesting review by a solid and robust team on invariance testing in Sturctural Equation Modeling.
    sciencedirect.com/science/arti