Nick Cheney
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How Weight Resampling and Optimizers Shape the Dynamics of Continual Learning and Forgetting in Neural Networks Open
Recent work in continual learning has highlighted the beneficial effect of resampling weights in the last layer of a neural network (``zapping"). Although empirical results demonstrate the effectiveness of this approach, the underlying mec…
The Genomic Code: the genome instantiates a generative model of the organism Open
How does the genome encode the form of the organism? What is the nature of this genomic code? Inspired by recent work in machine learning and neuroscience, we propose that the genome encodes a generative model of the organism. In this sche…
Reset It and Forget It: Relearning Last-Layer Weights Improves Continual and Transfer Learning Open
This work identifies a simple pre-training mechanism that leads to representations exhibiting better continual and transfer learning. This mechanism—the repeated resetting of weights in the last layer, which we nickname “zapping”—was origi…
No-brainer: Morphological Computation driven Adaptive Behavior in Soft Robots Open
It is prevalent in contemporary AI and robotics to separately postulate a brain modeled by neural networks and employ it to learn intelligent and adaptive behavior. While this method has worked very well for many types of tasks, it isn't t…
The Genomic Code: The genome instantiates a generative model of the organism Open
How does the genome encode the form of the organism? What is the nature of this genomic code? Inspired by recent work in machine learning and neuroscience, we propose that the genome encodes a generative model of the organism. In this sche…
Towards Multi-Morphology Controllers with Diversity and Knowledge Distillation Open
Finding controllers that perform well across multiple morphologies is an\nimportant milestone for large-scale robotics, in line with recent advances via\nfoundation models in other areas of machine learning. However, the challenges\nof lea…
LDCT image biomarkers that matter most for the deep learning classification of indeterminate pulmonary nodules Open
BACKGROUND Continued improvement in deep learning methodologies has increased the rate at which deep neural networks are being evaluated for medical applications, including diagnosis of lung cancer. However, there has been limited explorat…
Investigating Premature Convergence in Co-optimization of Morphology and Control in Evolved Virtual Soft Robots Open
Evolving virtual creatures is a field with a rich history and recently it has been getting more attention, especially in the soft robotics domain. The compliance of soft materials endows soft robots with complex behavior, but it also makes…
Networks of Binary Necklaces Induced by Elementary Cellular Automata Rules Open
Elementary cellular automata deterministically map a binary sequence to another using simple local rules. Visualizing the structure of this mapping is difficult because the number of nodes (i.e. possible binary sequences) grows exponential…
Assessing Free-Living Postural Sway in Persons With Multiple Sclerosis Open
Postural instability is associated with disease status and fall risk in Persons with Multiple Sclerosis (PwMS). However, assessments of postural instability, known as postural sway, leverage force platforms or wearable accelerometers, and …
The ChAMP App: A Scalable mHealth Technology for Detecting Digital Phenotypes of Early Childhood Mental Health Open
Childhood mental health problems are common, impairing, and can become chronic if left untreated. Children are not reliable reporters of their emotional and behavioral health, and caregivers often unintentionally under- or over-report chil…
Reset It and Forget It: Relearning Last-Layer Weights Improves Continual and Transfer Learning Open
This work identifies a simple pre-training mechanism that leads to representations exhibiting better continual and transfer learning. This mechanism -- the repeated resetting of weights in the last layer, which we nickname "zapping" -- was…
Assessing Free-Living Postural Sway in Persons with Multiple Sclerosis Open
Assessments of postural sway are associated with disease status and fall risk in Persons with Multiple Sclerosis (PwMS). However, these assessments, which leverage force platforms or wearable accelerometers, are most often conducted in lab…
Assessing Free-Living Postural Sway in Persons with Multiple Sclerosis Open
Assessments of postural sway are associated with disease status and fall risk in Persons with Multiple Sclerosis (PwMS). However, these assessments, which leverage force platforms or wearable accelerometers, are most often conducted in lab…
Many-objective Optimization via Voting for Elites Open
Real-world problems are often comprised of many objectives and require solutions that carefully trade-off between them. Current approaches to many-objective optimization often require challenging assumptions, like knowledge of the importan…
Coping with seasons: evolutionary dynamics of gene networks in a changing environment Open
In environments that vary frequently and unpredictably, bet-hedgers can\novertake the population. Diversifying bet-hedgers have a diverse set of\noffspring so that, no matter the conditions they find themselves in, at least\nsome offspring…
OmnImage: Evolving 1k Image Cliques for Few-Shot Learning Open
Few-shot learning datasets contain a large number of classes with only a few examples in each. Existing datasets may contain thousands of classes, but very simple images (e.g. handwritten characters) such that a naive baseline can perform …
Modular Controllers Facilitate the Co-Optimization of Morphology and Control in Soft Robots Open
Soft robotics is a rapidly growing area of robotics research that would\nbenefit greatly from design automation, given the challenges of manually\nengineering complex, compliant, and generally non-intuitive robot body plans\nand behaviors.…
Preterm Preeclampsia Risk Modelling: Examining Hemodynamic, Biochemical, and Biophysical Markers Prior to Pregnancy Open
Preeclampsia (PE) is a leading cause of maternal and perinatal death globally and can lead to unplanned preterm birth. Predicting risk for preterm or early-onset PE, has been investigated primarily after conception, and particularly in the…
Toward Digital Phenotypes of Early Childhood Mental Health via Unsupervised and Supervised Machine Learning Open
Childhood mental health disorders such as anxiety, depression, and ADHD are commonly-occurring and often go undetected into adolescence or adulthood. This can lead to detrimental impacts on long-term wellbeing and quality of life. Current …
Chest-Based Wearables and Individualized Distributions for Assessing Postural Sway in Persons with Multiple Sclerosis Open
Typical assessments of balance impairment are subjective or require data from cumbersome and expensive force platforms. Researchers have utilized lower back (sacrum) accelerometers to enable more accessible, objective measurement of postur…
Chest-Based Wearables and Individualized Distributions for Assessing Postural Sway in Persons with Multiple Sclerosis Open
Typical assessments of balance impairment are subjective or require data from cumbersome and expensive force platforms. Researchers have utilized lower back (sacrum) accelerometers to enable more accessible, objective measurement of postur…
The ChAMP App: A Scalable mHealth Technology for Detecting Digital Phenotypes of Early Childhood Mental Health Open
Childhood mental health problems are common, impairing, and can become chronic if left untreated. Children are not reliable reporters of their emotional and behavioral health, and caregivers often unintentionally under-or over-report child…
Connecting livestock disease dynamics to human learning and biosecurity decisions Open
The acceleration of animal disease spread worldwide due to increased animal, feed, and human movement has driven a growing body of epidemiological research as well as a deeper interest in human behavioral studies aimed at understanding the…
Digital Phenotypes of Instability and Fatigue Derived From Daily Standing Transitions in Persons With Multiple Sclerosis Open
Impairment in persons with multiple sclerosis (PwMS) can often be attributed to symptoms of motor instability and fatigue. Symptom monitoring and queued interventions often target these symptoms. Clinical metrics are currently limited to o…
Chest-Based Wearables and Individualized Distributions for Assessing Postural Sway in Persons With Multiple Sclerosis Open
Typical assessments of balance impairment are subjective or require data from cumbersome and expensive force platforms. Researchers have utilized lower back (sacrum) accelerometers to enable more accessible, objective measurement of postur…
Digital Phenotypes of Instability and Fatigue Derived from Daily Standing Transitions in Persons with Multiple Sclerosis Open
Impairment in persons with multiple sclerosis (PwMS) can often be attributed to symptoms of motor instability and fatigue. Symptom monitoring and queued interventions often target these symptoms. Clinical metrics are currently limited to o…
Digital Phenotypes of Instability and Fatigue Derived from Daily Standing Transitions in Persons with Multiple Sclerosis Open
Impairment in persons with multiple sclerosis (PwMS) can often be attributed to symptoms of motor instability and fatigue. Symptom monitoring and queued interventions often target these symptoms. Clinical metrics are currently limited to o…
View article: Open-source dataset reveals relationship between walking bout duration and fall risk classification performance in persons with multiple sclerosis
Open-source dataset reveals relationship between walking bout duration and fall risk classification performance in persons with multiple sclerosis Open
Falls are frequent and associated with morbidity in persons with multiple sclerosis (PwMS). Symptoms of MS fluctuate, and standard biannual clinical visits cannot capture these fluctuations. Remote monitoring techniques that leverage weara…