Tsuyoshi Okita

Where Individual-Effect Information Survives: A Diagnostic Ladder for World Models

World models are widely used for planning and control, but it remains unclear whether they can answer counterfactual questions of the form ``what would have happened to this individual under a different action.'' Such a question sits at the third rung of Pearl's ladder and requir...

Where Individual-Effect Information Survives: A Diagnostic Ladder for World Models

World models are widely used for planning and control, but it remains unclear whether they can answer counterfactual questions of the form ``what would have happened to this individual under a different action.'' Such a question sits at the third rung of Pearl's ladder and requir...

Adaptive Conformal Prediction with Foundation Models

Adaptive conformal prediction methods adjust prediction intervals online to maintain valid coverage under distribution shift. We study how predictor quality interacts with method effectiveness. We evaluate 21 conformal prediction methods and variants, including Conformal PID, SPC...

Imperfect Simulator Interventions: AI for Science

Computational simulators are increasingly used as surrogates for interventional experiments in causal discovery, but real-world simulators inevitably introduce variable omission, intervention noise, and structural misspecification. We show that a two-layer strategy---separating s...

Imperfect Simulator Interventions: AI for Science

Computational simulators are increasingly used as surrogates for interventional experiments in causal discovery, but real-world simulators inevitably introduce variable omission, intervention noise, and structural misspecification. We show that a two-layer strategy---separating s...

Adaptive Conformal Prediction with Foundation Models

Adaptive conformal prediction methods adjust prediction intervals online to maintain valid coverage under distribution shift. We study how predictor quality interacts with method effectiveness. We evaluate 21 conformal prediction methods and variants, including Conformal PID, SPC...

Sub-linear Power-Law Scaling of Information Processing Capacity in Noisy Physical Reservoirs

How does the computational capacity of a physical reservoir scale with the number of devices? This paper quantifies the dependence of information processing capacity (IPC) on device count under device noise identified from hardware measurements and reports three findings. (1)~IPC...

Sub-linear Power-Law Scaling of Information Processing Capacity in Noisy Physical Reservoirs

How does the computational capacity of a physical reservoir scale with the number of devices? This paper quantifies the dependence of information processing capacity (IPC) on device count under device noise identified from hardware measurements and reports three findings. (1)~IPC...

Multi-instance Learning as Downstream Task of Self-Supervised Learningbased Pre-trained Model

In deep multi-instance learning, the number of applicable instances depends on the data set. In histopathology images, deep learning multi-instance learners usually assume there are hundreds to thousands instances in a bag. However, when the number of instances in a bag increases...