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in contrast the plug-in approach is based on regression where one first estimates the conditional average treatment effect cate and then recommends the
treatment
treatment effect
in contrast the plug-in approach is based on regression where one first estimates the conditional average treatment effect cate and then recommends the treatment with the highest estimated outcome
a popular opinion is that much of the contextual influences arise from feedback from higher visual
areas
cognitive neuroscience
a popular opinion is that much of the contextual influences arise from feedback from higher visual areas whose neurons have larger receptive fields
this thesis presents a first-principles study of excitons in
two-dimensional
quantum materials
this thesis presents a first-principles study of excitons in two-dimensional materials
our results herald the use of quantum computing for simulating strongly correlated
electronic
quantum batteries
our results herald the use of quantum computing for simulating strongly correlated electronic systems beyond the capacity of classical computing
keywords co-ranking sep partitioning sep merge-free algorithms sep index-space optimization sep selection and merging sep
data
compressed indexing
keywords co-ranking sep partitioning sep merge-free algorithms sep index-space optimization sep selection and merging sep data structures
we demonstrate triggering of a quantum dot qd single photon
emission
quantum emitters
we demonstrate triggering of a quantum dot qd single photon emission using dynamic purcell effect induced at a frequency of several ghz by acoustic strain
we evaluate csi2q on one synthetic csi dataset involving 85 devices and two real
csi
csi dataset
we evaluate csi2q on one synthetic csi dataset involving 85 devices and two real csi datasets including 10 and 25 wifi routers respectively
optical flow produces spatially continuous drift fields providing
motion
optical flow
optical flow produces spatially continuous drift fields providing motion estimates for every image pixel rather than at sparse buoy locations offering new opportunities for navigation and climate modeling
whereas generic dnn cannot guarantee accuracy outside the
training
neural network
whereas generic dnn cannot guarantee accuracy outside the training distribution the closed-form nn model produces exact solutions for every discovered critical region of the solution function
a prevailing theory in cognitive neuroscience proposes that the human brain operates through hierarchical predictive processing which underlies flexible
cognition
human cognition
a prevailing theory in cognitive neuroscience proposes that the human brain operates through hierarchical predictive processing which underlies flexible cognition and behavior by integrating multimodal sensory signals
we present a systematic comparison of three independent machine learning ml -based searches for strong gravitational lenses applied to the
dark
dark matter
we present a systematic comparison of three independent machine learning ml -based searches for strong gravitational lenses applied to the dark energy survey jacobs et al
specifically we prove a fundamental theorem that characterizes the optimal
inference
language models
specifically we prove a fundamental theorem that characterizes the optimal inference time for multi-model speculative decoding systems shedding light on how to extend beyond the dualistic approach to a more general polybasic paradigm
in the cold dark environments of pre-stellar cores where the temperatures are below 10 k ne can condense onto the surface of
interstellar
dwarf galaxies
in the cold dark environments of pre-stellar cores where the temperatures are below 10 k ne can condense onto the surface of interstellar grains
these improvements underscore ssf s ability to deliver robust low-overhead feedback and adaptability to support a wide range of
isac
communication isac
these improvements underscore ssf s ability to deliver robust low-overhead feedback and adaptability to support a wide range of isac applications
we give the first super-constant bound to this problem demonstrating an example with a coding advantage of
omega
omega log
we give the first super-constant bound to this problem demonstrating an example with a coding advantage of omega log k
we establish the validity of bootstrap methods for empirical likelihood el inference under the
density
density estimation
we establish the validity of bootstrap methods for empirical likelihood el inference under the density ratio model drm
convergence of a relative-type inexact proximal alm for
convex
strongly convex
convergence of a relative-type inexact proximal alm for convex nonlinear programming
deep learning-based csi prediction framework for
channel
channel estimation
deep learning-based csi prediction framework for channel aging mitigation in tdd 5g systems
while modern large language models llms are increasingly used to model neural responses to
language
recurrent neural
while modern large language models llms are increasingly used to model neural responses to language their internal representations are highly entangled mixing information about lexicon syntax meaning and reasoning
by reparameterizing the diffusion process with an incorporated energy function the framework explicitly estimates the unnormalized log-prior while mh corrections refine the sampling trajectory mitigate deviations and enhance robustness ultimately enabling accurate posterior sampling for high-fidelity
channel
channel state information
by reparameterizing the diffusion process with an incorporated energy function the framework explicitly estimates the unnormalized log-prior while mh corrections refine the sampling trajectory mitigate deviations and enhance robustness ultimately enabling accurate posterior sampling for high-fidelity channel estimation
this study presents a comprehensive data-driven framework that learns his via two learning approaches integrated with multi-domain
signal
signal processing
this study presents a comprehensive data-driven framework that learns his via two learning approaches integrated with multi-domain signal processing
if this powerful ai is to serve the needs of consumers voters and
decision
artificial intelligence
if this powerful ai is to serve the needs of consumers voters and decision makers then it is imperative that the ai is accountable
we confirm that galaxies with star formation efficiencies lower than the
milky
galactic disk
we confirm that galaxies with star formation efficiencies lower than the milky way have high probably indicating a stronger efficiency of the delayed sources of r-process at low metallicities
most ai systems today are designed to manage
tasks
ai assistance
most ai systems today are designed to manage tasks and execute predefined steps
experimental verification is scarce however especially in the telecom range because real
photonic
photonic crystal
experimental verification is scarce however especially in the telecom range because real photonic crystals and experimental methods inherently cannot be homogeneous in the third dimension
the second-order stark shift exceeds 10 ghz which is of the same order of magnitude as the 15
ghz
ghz ghz
the second-order stark shift exceeds 10 ghz which is of the same order of magnitude as the 15 ghz inhomogeneous distribution of siv - observed in emitters embedded in optical nanostructures such as photonic crystal nanocavities
in particular systems with bounded positive orbits admit a compact
control
control systems
in particular systems with bounded positive orbits admit a compact control set and if the system is controllable the entire state space is a compact group
using modern fast pixelated electron detectors we were able to acquire rapidly a large number of low noise
electron
electron microscopy
using modern fast pixelated electron detectors we were able to acquire rapidly a large number of low noise electron diffraction patterns of swcnts
deep learning-based approaches have achieved strong performance but typically rely
heavily
deep learning
deep learning-based approaches have achieved strong performance but typically rely heavily on extensive training data and often fail to generalize to unseen signals
we simulated data to reflect real-world scenarios with differing levels of confounding sample size and nco
confounding
synthetic data
we simulated data to reflect real-world scenarios with differing levels of confounding sample size and nco confounding structures
however current evaluations of llm-based persona
simulation
persona simulation
however current evaluations of llm-based persona simulation remain limited most rely on synthetic dialogues lack systematic frameworks and lack analysis of the capability requirement
order-unity star formation efficiencies sfe in early galaxies may explain the overabundance of bright galaxies observed by
jwst
active galactic
order-unity star formation efficiencies sfe in early galaxies may explain the overabundance of bright galaxies observed by jwst at high redshift
this simulation pipeline is co-designed with a dual-head multi-scale reconstruction network that employs a shared encoder to jointly recover a high-fidelity all-in-focus aif
image
depth estimation
this simulation pipeline is co-designed with a dual-head multi-scale reconstruction network that employs a shared encoder to jointly recover a high-fidelity all-in-focus aif image and a precise depth map from a single coded capture
however as typical to any quantum resource
network
quantum networks
however as typical to any quantum resource network nonlocality is also vulnerable to environmental noise which sometimes prove to be detrimental
we present a framework for the analysis of object-aware controllers methods for altering a
robot
dynamic obstacles
we present a framework for the analysis of object-aware controllers methods for altering a robot s motion to anticipate and avoid possible collisions
because observational inputs may be biased in ways unknown ex ante we
develop
debiased machine learning
because observational inputs may be biased in ways unknown ex ante we develop a minimax proportional regret objective that evaluates any candidate design relative to an oracle that knows the bias and jointly chooses the design and estimator
our analysis loosely favours local starburst
activity
star formation rates
our analysis loosely favours local starburst activity as the driver of the shocks and circumnuclear gas dynamics in ngc 7582 though the possibility of an agn jet contribution cannot be excluded
we present brain-it a brain-inspired approach that addresses this challenge through a brain interaction transformer bit allowing effective
interactions
brain activity
we present brain-it a brain-inspired approach that addresses this challenge through a brain interaction transformer bit allowing effective interactions between clusters of functionally-similar brain-voxels
we consider the problem of density estimation in the context of multiscale langevin
diffusion
diffusion models
we consider the problem of density estimation in the context of multiscale langevin diffusion processes where a single-scale homogenized surrogate model can be derived
3d objects and maps falling short of full end-to-end learning from raw
sensor
sensor data
3d objects and maps falling short of full end-to-end learning from raw sensor data
we show that while o vi emission primarily originates in inflowing gas turning off outflows in a simulation without star formation feedback eliminates most of the
o
emission line
we show that while o vi emission primarily originates in inflowing gas turning off outflows in a simulation without star formation feedback eliminates most of the o vi emission
thus any algorithm for average distance in constant degree graphs whose approximation guarantee is less than 4 must query omega n 2 distances any such algorithm whose approximation guarantee is less than 6 must query omega n 3 2 distances any such algorithm whose approximation
guarantee
approximation guarantee
thus any algorithm for average distance in constant degree graphs whose approximation guarantee is less than 4 must query omega n 2 distances any such algorithm whose approximation guarantee is less than 6 must query omega n 3 2 distances any such algorithm whose approximation guarantee less than 8 must query omega n 4...
from classical to active particles mathematical
tools
statistical physics
from classical to active particles mathematical tools for social dynamics and behavioural economics
we study the fundamental question of how efficiently suffix array entries can be accessed when the
array
suffix array
we study the fundamental question of how efficiently suffix array entries can be accessed when the array cannot be stored explicitly
our parallel algorithm computes the union intersection and difference of two b-trees with o m log_b n m i o work and o log_b m cdot log_2 log_b n log_b n i o span where n and m leq n are the sizes of the two
trees
spanning trees
our parallel algorithm computes the union intersection and difference of two b-trees with o m log_b n m i o work and o log_b m cdot log_2 log_b n log_b n i o span where n and m leq n are the sizes of the two trees and b is the block size
two-dimensional 2d materials offer large-area atomically flat surfaces suitable for massively parallel in-plane biomolecule
imaging
atomic force microscopy
two-dimensional 2d materials offer large-area atomically flat surfaces suitable for massively parallel in-plane biomolecule imaging yet achieving guided motion in one-dimensional confinements using top-down nanofabrication remains challenging
braincognizer brain decoding with human visual
cognition
human cognition
braincognizer brain decoding with human visual cognition simulation for fmri-to-image reconstruction
many believe that intracortical axons conduct signals too slowly to bring the contextual information from
receptive
visual stimuli
many believe that intracortical axons conduct signals too slowly to bring the contextual information from receptive fields of other neurons
by using the meta-algorithm with the measured continuous greedy algorithm we
obtain
-approximation algorithm
by using the meta-algorithm with the measured continuous greedy algorithm we obtain a 1-1 e -approximation resp
a popular opinion is that much of the contextual influences arise from feedback from higher visual areas whose neurons have larger
receptive
higher-order visual
a popular opinion is that much of the contextual influences arise from feedback from higher visual areas whose neurons have larger receptive fields
the advent of mass measurements of radial velocities of stars has recently led to a number of interesting results obtained from the analysis of spatial velocities of
stars
stellar population
the advent of mass measurements of radial velocities of stars has recently led to a number of interesting results obtained from the analysis of spatial velocities of stars and open star clusters
calibration has emerged as a foundational goal in
trustworthy
machine learning
calibration has emerged as a foundational goal in trustworthy machine learning in part because of its strong decision theoretic semantics
education unexpectedly has now become burdened by an especially crucial role of charting long-range strategies for discovering viable human skills that would guarantee their place in the world of the ubiquitous use of ai in the
intellectual
artificial intelligence
education unexpectedly has now become burdened by an especially crucial role of charting long-range strategies for discovering viable human skills that would guarantee their place in the world of the ubiquitous use of ai in the intellectual sphere
by experimental results pvmark efficiently enables public verifiability on the state-of-the-art llm watermarking schemes yet without compromising the
watermarking
watermarking schemes
by experimental results pvmark efficiently enables public verifiability on the state-of-the-art llm watermarking schemes yet without compromising the watermarking performance promising to be deployed in practice
in this work we explore the sequence of pressure- and temperature-driven
phase
phase transition
in this work we explore the sequence of pressure- and temperature-driven phase transitions in hh focusing on the interplay between molecular rotation orientational ordering lattice symmetry breaking and hydrogen bond symmetrization
the alignment trend becomes particularly pronounced in regions of high
tidal
tidal field
the alignment trend becomes particularly pronounced in regions of high tidal anisotropy and high overdensity
6 thin films studied by xray reflectivity and hard
xray
photoemission spectroscopy
6 thin films studied by xray reflectivity and hard xray photoemission
we find that independently of their gas surface density sigma_g clouds are disrupted on a timescale shorter than a free-fall
time
star formation rates
we find that independently of their gas surface density sigma_g clouds are disrupted on a timescale shorter than a free-fall time and even before supernova explosions if sigma_g gtrsim 10 3 m_ odot rm pc -2
more recently a new class of prefix queries was introduced together with reductions that among others transform a simple tradeoff for prefix-select queries into a suffix
array
suffix array
more recently a new class of prefix queries was introduced together with reductions that among others transform a simple tradeoff for prefix-select queries into a suffix array tradeoff matching state-of-the-art space and query-time bounds while achieving sublinear construction time
furthermore to enhance the adaptive optimization capability of the
context
context length
furthermore to enhance the adaptive optimization capability of the context length we present an efficient input representation for the central agent which effectively filters redundant information
we define symmetric and asymmetric branching trees a class of processes particularly suited for modeling genealogies of inhomogeneous
populations
population genetics
we define symmetric and asymmetric branching trees a class of processes particularly suited for modeling genealogies of inhomogeneous populations where individuals may reproduce throughout life
however this trajectory-to-trajectory formulation often entangles camera
motion
optical flow
however this trajectory-to-trajectory formulation often entangles camera motion with scene dynamics and complicates both modeling and inference
that decode specific relational facts in transformer
language
natural language
that decode specific relational facts in transformer language models
the intercalation of guest species into the gap of van
der
van der waals
the intercalation of guest species into the gap of van der waals materials often leads to the emergence of intriguing phenomena such as superconductivity
in these models the retrieval of a particular memory can be hampered by overlaps between the network state and other memories termed spurious overlaps since these overlaps collectively introduce noise in the
retrieval
memory demand
in these models the retrieval of a particular memory can be hampered by overlaps between the network state and other memories termed spurious overlaps since these overlaps collectively introduce noise in the retrieval process
sampling from log-concave distributions is a central problem in statistics and
machine
debiased machine learning
sampling from log-concave distributions is a central problem in statistics and machine learning
we apply our method to variational quantum
algorithm
quantum networks
we apply our method to variational quantum algorithm vqa ansatz design for molecular ground state estimation max-cut and image classification key challenges in near-term quantum computing
a toy model-based experiment shows that def can identify multiple
patterns
beam pattern
a toy model-based experiment shows that def can identify multiple patterns with distinct lengths
here we perform a non-perturbative circuit analysis in terms of dressed transmission-line modes for representative resonant
coupling
s-o coupling
here we perform a non-perturbative circuit analysis in terms of dressed transmission-line modes for representative resonant coupling circuits going beyond the weak-coupling treatment
the goal of policy learning is to train a
policy
policy evaluation
the goal of policy learning is to train a policy function that recommends a treatment given covariates to maximize population welfare
that decode specific relational facts in transformer
language
language models
that decode specific relational facts in transformer language models
in contrast the plug-in approach is based on regression where one first estimates the conditional average treatment effect cate and then recommends the
treatment
treatment effect
in contrast the plug-in approach is based on regression where one first estimates the conditional average treatment effect cate and then recommends the treatment with the highest estimated outcome
with an average physical resolution of 17 pc this is one of the largest samples of highly resolved spectrally mapped extragalactic
hii
hii regions
with an average physical resolution of 17 pc this is one of the largest samples of highly resolved spectrally mapped extragalactic hii regions
robust variable selection for spatial point
processes
variable selection
robust variable selection for spatial point processes observed with noise
the results demonstrate the power benefits of
resolution
temporal resolution
the results demonstrate the power benefits of resolution reconfigurable front-ends and their wide applicability to neural decoding problems
rather than discrete treatment effect estimators the framework characterizes treatment intensity as a
continuous
treatment effect
rather than discrete treatment effect estimators the framework characterizes treatment intensity as a continuous function tau mathbf x t over space-time enabling rigorous analysis of propagation dynamics boundary evolution and cumulative exposure patterns
thus any algorithm for average distance in constant degree
graphs
-approximation algorithm
thus any algorithm for average distance in constant degree graphs whose approximation guarantee is less than 4 must query omega n 2 distances any such algorithm whose approximation guarantee is less than 6 must query omega n 3 2 distances any such algorithm whose approximation guarantee less than 8 must query omega n 4...
geometric priors are incorporated into image annotations to constrain the vlm
action
vision-language-action vla
geometric priors are incorporated into image annotations to constrain the vlm action space and improve decision quality
we introduce rlmeval an evaluation suite for these tasks focusing on research-level mathematics from real-world
lean
open-source models
we introduce rlmeval an evaluation suite for these tasks focusing on research-level mathematics from real-world lean formalization projects
this allows us to infer a dense turn-by-turn reward signal grounded in the expert s revealed strategy decomposing the intractable long-horizon problem into a series of supervised
learning
reinforcement learning rl
this allows us to infer a dense turn-by-turn reward signal grounded in the expert s revealed strategy decomposing the intractable long-horizon problem into a series of supervised learning tasks and training a policy to output a structured texttt action state_assessment tuple governing both textbf what to ask and crucia...
the agent learns to ask when uncertain and the human
learns
policy learning
the agent learns to ask when uncertain and the human learns when to oversee leading to an emergent collaboration that avoids safety violations introduced post-training
in this work we propose portool a reinforcement
learning
reinforcement learning
in this work we propose portool a reinforcement learning rl method that encourages a tool-use llm to explore various trajectories yielding the correct answer
by openly releasing all models datasets code and checkpoints gaperon establishes a reproducible foundation for exploring the trade-offs between data curation evaluation safety and openness in
multilingual
multilingual data
by openly releasing all models datasets code and checkpoints gaperon establishes a reproducible foundation for exploring the trade-offs between data curation evaluation safety and openness in multilingual language model development
the classic exact pattern matching problem given two strings -- a
pattern
pattern matching
the classic exact pattern matching problem given two strings -- a pattern p of length m and a text t of length n -- asks whether p occurs as a substring of t
a dynamic reasoning module refines predictions by combining global
scene
multimodal reasoning
a dynamic reasoning module refines predictions by combining global scene cues and object-level interactions guided by linguistic priors
collision avoidance and path finding in a
robotic
multi-robot collaboration
collision avoidance and path finding in a robotic mobile fulfillment system using multi-objective meta-heuristics
this is important as reliable navigation around other vehicles is vital for
safe
obstacle avoidance
this is important as reliable navigation around other vehicles is vital for safe autonomous wheel-to-wheel racing
to tackle this challenge we propose braincognizer a novel brain decoding model inspired by human visual
cognition
human brain
to tackle this challenge we propose braincognizer a novel brain decoding model inspired by human visual cognition which explores multi-level semantics and correlations without fine-tuning of generative models
introduced by korpelevich in 1976 the extragradient method eg has become a cornerstone technique for
solving
augmented lagrangian
introduced by korpelevich in 1976 the extragradient method eg has become a cornerstone technique for solving min-max optimization root-finding problems and variational inequalities vis
to overcome these challenges we then develop a generic synthesis framework based on the flow of neural dynamics
drift
recurrent neural
to overcome these challenges we then develop a generic synthesis framework based on the flow of neural dynamics drift enabling explicit piecewise constant and constant-in-time inputs
overall seq-deepipc extends end-to-end navigation beyond wheeled robots to more
versatile
autonomous driving
overall seq-deepipc extends end-to-end navigation beyond wheeled robots to more versatile and temporally-aware systems
we show here that in models equipped with a learning rule inferred from neurobiological data spurious overlaps collectively reduce the mean synaptic inputs to
neurons
neural codes
we show here that in models equipped with a learning rule inferred from neurobiological data spurious overlaps collectively reduce the mean synaptic inputs to neurons and that this mean reduction causes in turn an increase in storage capacity through a sparsening of network activity
n alpha demonstrate an optimal region of relaxation and dephasing where coherent driving stabilizes entanglement
entropy
entanglement entropy
n alpha demonstrate an optimal region of relaxation and dephasing where coherent driving stabilizes entanglement entropy growth for thermodynamic observables maximum energy e_ mathrm max charging time tau and maximum power bar p _ mathrm max and for qubit and cavity entanglement entropies
we study bilevel optimization problems where the lower-level problems are strongly convex and have coupled
linear
quadratic programming
we study bilevel optimization problems where the lower-level problems are strongly convex and have coupled linear constraints
our findings introduce a new paradigm in integrated
photonics
integrated photonics
our findings introduce a new paradigm in integrated photonics paving the way for ultracompact modulators and highly tunable on-chip communication systems with reduced power consumption
graph-theoretical mapping of resting-state
eeg
brain activity
graph-theoretical mapping of resting-state eeg reveals neural signatures of creativity
in the present paper we report an enhancement of
ionic
ionic conduction
in the present paper we report an enhancement of ionic conductivity in cu2p2-xvxo7 by vanadium substitution
in this study we used a data-driven network approach to examine whether resting-state
eeg
cognitive neuroscience
in this study we used a data-driven network approach to examine whether resting-state eeg connectivity patterns differentiate individuals according to their creative abilities
process-level trajectory evaluation for environment
configuration
environment configuration
process-level trajectory evaluation for environment configuration in software engineering agents
this paper proposes a coherence-aware communication-efficient framework for joint
channel
channel estimation
this paper proposes a coherence-aware communication-efficient framework for joint channel training and model updating in practical wireless fl systems operating under heterogeneous fading dynamics