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in this study we develop a continuous time markov chain model to assess the probability of long-term chikungunya establishment in miami-dade county following repeated introductions of external
infectious
infectious individuals
in this study we develop a continuous time markov chain model to assess the probability of long-term chikungunya establishment in miami-dade county following repeated introductions of external infectious individuals
we apply inputdsa on recurrent neural networks
rnns
neural representations
we apply inputdsa on recurrent neural networks rnns trained with deep reinforcement learning identifying that high-performing networks are dynamically similar to one another while low-performing networks are more diverse
these features suggest that the gas forming the cold front is flowing in the plane oriented along the los supporting an offset merger scenario in which the main
cluster
star-forming region
these features suggest that the gas forming the cold front is flowing in the plane oriented along the los supporting an offset merger scenario in which the main cluster has passed in front of the subcluster and induced rotation of the core gas in the plane perpendicular to the sky
human feedback is critical for aligning ai systems to
human
artificial intelligence
human feedback is critical for aligning ai systems to human values
here we present mobilitygen a deep generative model that produces realistic
mobility
human mobility
here we present mobilitygen a deep generative model that produces realistic mobility trajectories spanning days to weeks at large spatial scales
the global encoder captures global semantic features from the entire image while the local
encoder
cross dual encoder network
the global encoder captures global semantic features from the entire image while the local encoder focuses on features from the prior network
in this paper we consider high-dimensional
lp-quantile
quantile regression
in this paper we consider high-dimensional lp-quantile regression which only requires a low order moment of the error and is also a natural generalization of the above methods and lp-regression as well
we design a deterministic algorithm that given n points in a emph typical constant degree regular graph
queries
query complexity
we design a deterministic algorithm that given n points in a emph typical constant degree regular graph queries o n distances to output a constant factor approximation to the average distance among those points thus answering a question posed in cite mn14
under some regularity conditions we show that beta_n s_n the mle of the unknown regression vector beta_0 and the scale s_0 exists and give the expression of the
asymptotic
asymptotic normality
under some regularity conditions we show that beta_n s_n the mle of the unknown regression vector beta_0 and the scale s_0 exists and give the expression of the asymptotic efficiency of beta_n over the olse
to evaluate llms ability to identify and redact such private information
prior
models llms
to evaluate llms ability to identify and redact such private information prior work developed benchmarks e
information-theoretically retrieval data structures can use as little as nv
bits
data structure
information-theoretically retrieval data structures can use as little as nv bits of space
modeling and scheduling of fusion patterns in
autonomous
collision avoidance
modeling and scheduling of fusion patterns in autonomous driving systems extended version
on quantile treatment effects rank similarity and variation of
instrumental
instrumental variable
on quantile treatment effects rank similarity and variation of instrumental variables
in the latter case we show that coexistence of both strains is impossible when mutation occurs from the strain with lower
reproduction
reproduction number
in the latter case we show that coexistence of both strains is impossible when mutation occurs from the strain with lower reproduction number and transmission rate to the other strain
the cost function of the mhe optimization
problem
inverse optimal
the cost function of the mhe optimization problem is suitably designed to accommodate these irregular output sequences
enhancing the reachability of variational quantum
algorithms
quantum channels
enhancing the reachability of variational quantum algorithms via input-state design
in this paper a new method for geometric robot calibration is introduced which uses a
calibration
calibration plate
in this paper a new method for geometric robot calibration is introduced which uses a calibration plate with precisely known distances between its measuring points
we first provide a formulation of the data-generating process assuming that the
observed
synthetic data
we first provide a formulation of the data-generating process assuming that the observed data e
a prevailing theory in cognitive neuroscience proposes that the human brain operates through hierarchical predictive processing which underlies flexible
cognition
cognitive science
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
3d human pose estimation from sketches has broad applications in computer
animation
pose estimation
3d human pose estimation from sketches has broad applications in computer animation and film production
the second development step is carbonization of the matrix just near the gold nanoparticles performed by homogeneous irradiation of the recorded pattern by the powerful radiation of the
second
pulsed laser
the second development step is carbonization of the matrix just near the gold nanoparticles performed by homogeneous irradiation of the recorded pattern by the powerful radiation of the second harmonic of the same laser
in this work we show that the quantum walk technique fails to produce a fast
algorithm
quantum error correction
in this work we show that the quantum walk technique fails to produce a fast algorithm improving the known or even the trivial upper bound on the query complexity
starting from fundamental fluid dynamics equations navier-stokes we derive conditions under which treatment effects
decay
spatial decay
starting from fundamental fluid dynamics equations navier-stokes we derive conditions under which treatment effects decay exponentially in space and time enabling researchers to calculate explicit boundaries beyond which effects become undetectable
next we assign rewards to each step based on its ability to produce a
correct
reinforcement learning rl
next we assign rewards to each step based on its ability to produce a correct answer and make successful tool calls
contribution of task-irrelevant stimuli to
drift
continual learning
contribution of task-irrelevant stimuli to drift of neural representations
we introduce orchvis a multi-agent orchestration framework that visualizes verifies and coordinates goal-driven
collaboration
ai agents
we introduce orchvis a multi-agent orchestration framework that visualizes verifies and coordinates goal-driven collaboration among llm-based agents
the simulation results validate the framework s ability to simultaneously manage both hard and soft
constraints
soft constraints
the simulation results validate the framework s ability to simultaneously manage both hard and soft constraints in safety-critical settings
to this end we introduce a new dataset covering a wide range of formal patterns of reasoning in both
normative
reasoning capabilities
to this end we introduce a new dataset covering a wide range of formal patterns of reasoning in both normative and epistemic domains while also incorporating non-formal cognitive factors that influence human reasoning
inputdsa demixing then comparing recurrent and externally
driven
inner speech
inputdsa demixing then comparing recurrent and externally driven dynamics
empirically we find that infonce-anchor with the log score achieves the most accurate mi estimates however in self-supervised representation learning
experiments
predictive performance
empirically we find that infonce-anchor with the log score achieves the most accurate mi estimates however in self-supervised representation learning experiments we find that the anchor does not improve the downstream task performance
the framework replicates both inaction in the case of
climate
climate change
the framework replicates both inaction in the case of climate change mitigation as well as the faster response that we exhibited to covid-19
in this paper we introduce an evaluation model to assess the value of
travel
travel information
in this paper we introduce an evaluation model to assess the value of travel information under different scenarios
in addition to the exact result for the mathcal r_0 we provide an approximation denoted as tau which is easier to compute and more straightforward to interpret in terms of the parameters of the system and shares most of the expected properties of the basic
reproduction
reproduction number
in addition to the exact result for the mathcal r_0 we provide an approximation denoted as tau which is easier to compute and more straightforward to interpret in terms of the parameters of the system and shares most of the expected properties of the basic reproduction number
in the cold dark environments of pre-stellar cores where the temperatures are below 10 k ne can condense onto the surface of
interstellar
interstellar medium
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
cypress crop yield prediction via regression on prithvi s
encoder
yield prediction
cypress crop yield prediction via regression on prithvi s encoder for satellite sensing
the time-domain projections are fourier transformed to provide frequency domain slices that can be fit to slices of
experimental
spectral range
the time-domain projections are fourier transformed to provide frequency domain slices that can be fit to slices of experimental spectra
our findings reveal that while current video models demonstrate promising reasoning patterns on short-horizon spatial coherence fine-grained grounding and locally consistent dynamics they remain limited in long-horizon causal
reasoning
temporal understanding
our findings reveal that while current video models demonstrate promising reasoning patterns on short-horizon spatial coherence fine-grained grounding and locally consistent dynamics they remain limited in long-horizon causal reasoning strict geometric constraints and abstract logic
emergence evolution and manipulation of swing
voters
swing voters
emergence evolution and manipulation of swing voters in presidential election
existing approaches from vision-language-action
vla
vla models
existing approaches from vision-language-action vla models to hierarchical frameworks fall short due to their reliance on limited or dividual-agent memory
this paper introduces a simple code-agnostic framework that reduces the worst-case
complexity
query complexity
this paper introduces a simple code-agnostic framework that reduces the worst-case complexity by a factor of n down to q k operations a highly desirable reduction in practice
results show that unlike all other computational processes
consciousness
surrogate brain
results show that unlike all other computational processes consciousness is not independent of its substrate and possessing it is an evolutionary advantage for intelligent entities
the orbital angular momentum oam of light is a versatile degree of freedom with transformative impact across optical communication
imaging
nonlinear optical
the orbital angular momentum oam of light is a versatile degree of freedom with transformative impact across optical communication imaging and micromanipulation
here by composing scale-invariant networks we show how tinkering decouples fiedler and
spectral
scale-free networks
here by composing scale-invariant networks we show how tinkering decouples fiedler and spectral dimensions hitherto considered identical providing valuable insights into mesoscopic and macroscopic collective regimes
we propose a mathematically principled pde
gradient
gradient descent
we propose a mathematically principled pde gradient flow framework for distributionally robust optimization dro
fair rate maximization for multi-user multi-cell miso
communication
communication systems
fair rate maximization for multi-user multi-cell miso communication systems via novel transmissive ris transceiver
it not only provides a more quality foundational network framework for network research but also serve as the brand
new
complex networks
it not only provides a more quality foundational network framework for network research but also serve as the brand new paradigm for bridging the conceptual divide between various classical network models
watermarking schemes for large language models
llms
large language models llms
watermarking schemes for large language models llms have been proposed to identify the source of the generated text mitigating the potential threats emerged from model theft
we formulate the problem as the minimization of the total transmit
power
transmit power
we formulate the problem as the minimization of the total transmit power subject to signal-to-interference-plus-noise ratio sinr constraints for communication users and mean-squared-error mse constraints for radar sensing
in this work we extend our previous work on the extrapolation of single-time observables to demonstrate an efficient scheme for
computing
quantum coherence
in this work we extend our previous work on the extrapolation of single-time observables to demonstrate an efficient scheme for computing two-time impurity correlation functions by combining the non-markovian quantum mpemba effect nmqmpe with a dynamical map-based framework for open quantum systems
in contrast for the two lowest bands the rashba-like
coupling
magnetic anisotropy
in contrast for the two lowest bands the rashba-like coupling becomes strongly anisotropic
heat conduction and radiation are two of the three
fundamental
heat conduction
heat conduction and radiation are two of the three fundamental modes of heat transfer playing a critical role in a wide range of scientific and engineering applications ranging from energy systems to materials science
we show that if the system is controllable then incorporating this as
prior
predictive control
we show that if the system is controllable then incorporating this as prior knowledge does not relax the conditions required for data-driven stabilization
our findings thus interpret linear relational
decoding
language models
our findings thus interpret linear relational decoding in transformer language models as primarily property-based rather than relation-specific
finding a computational model has proven elusive particularly because of conflation of consciousness with other
cognitive
cognitive science
finding a computational model has proven elusive particularly because of conflation of consciousness with other cognitive capabilities exhibited by humans such as intelligence and physiological sensations
we find that combining ai ratings and human ratings based on ai rater
confidence
trustworthy ai
we find that combining ai ratings and human ratings based on ai rater confidence is better than relying on either alone
using this principle we demonstrate continuous tuning of a large-area metasurface for
continuous
beam shaping
using this principle we demonstrate continuous tuning of a large-area metasurface for continuous beam-steering without per-meta-atom phase actuation
results indicated that the pulsed wave mode enhanced the global efficiency local efficiency and betweenness centrality of microstate c in brain
functional
functional connectivity
results indicated that the pulsed wave mode enhanced the global efficiency local efficiency and betweenness centrality of microstate c in brain functional networks as well as the mean durations parameter achieving a middle to large effect size with superior effects compared to the sham and continuous wave groups
moreover we identify a structural frontier for tractability by showing that the problem is solvable in
polynomial
polynomial time
moreover we identify a structural frontier for tractability by showing that the problem is solvable in polynomial time on graphs of bounded bandwidth
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
photonic crystal
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
we quantify the gas flows from a scale of up to several parsecs down to the sub-parsec scale along filamentary structures in the three
high-mass
massive stars
we quantify the gas flows from a scale of up to several parsecs down to the sub-parsec scale along filamentary structures in the three high-mass star-forming regions g75
to investigate the neural representations that
emerge
deep learning
to investigate the neural representations that emerge in these networks we develop an analytical framework that maps the optimization over the network weights into a mean-field problem over the distribution of neural preactivations
results from perturbation theory along with lyapunov stability and eigen-spectrum analysis are used to prove the
convergence
linear convergence
results from perturbation theory along with lyapunov stability and eigen-spectrum analysis are used to prove the convergence towards the optimal case
however in the place condition such a shift is missing presumably because most of the regions that are sensitive to task performance in the place
condition
task performance
however in the place condition such a shift is missing presumably because most of the regions that are sensitive to task performance in the place condition are in the lower end of the s-a axis
ops problems are computationally challenging mixed-integer linear programs milps that must be
solved
efficiently solving
ops problems are computationally challenging mixed-integer linear programs milps that must be solved rapidly and frequently in operational settings
specifically we focus on downlink dl bistatic sensing where the user equipment ue performs measurements from reflected
sensing
uplink communication
specifically we focus on downlink dl bistatic sensing where the user equipment ue performs measurements from reflected sensing signals and provides feedback to the network nw
ais have made rapid progress on research-oriented benchmarks of
knowledge
reasoning capabilities
ais have made rapid progress on research-oriented benchmarks of knowledge and reasoning but it remains unclear how these gains translate into economic value and automation
braincognizer brain decoding with human visual
cognition
fmri data
braincognizer brain decoding with human visual cognition simulation for fmri-to-image reconstruction
we present a simple pipeline that i generates a large set of wavelength demultiplexers wdms with spins-b ii records each final 2d layout and its
spectral
optical communication
we present a simple pipeline that i generates a large set of wavelength demultiplexers wdms with spins-b ii records each final 2d layout and its spectral metrics e
to generate physically and semantically plausible supervision
signals
predictive processing
to generate physically and semantically plausible supervision signals we introduce a spatial prior labeling method that guides a vision-language model to produce reasonable manipulation orders for distillation
finally we outline several potential applications of nonlinear sis in
wireless
wireless systems
finally we outline several potential applications of nonlinear sis in wireless communication scenarios
furthermore we also characterize quantum channels according to their ability in preserving quantum
resources
entanglement entropy
furthermore we also characterize quantum channels according to their ability in preserving quantum resources i
we find that dwarf agn selected by infrared colors are the most distinct
population
star formation rates
we find that dwarf agn selected by infrared colors are the most distinct population with the highest star formation rates and lowest stellar masses
our novel approach expands the capabilities of the
robot
imitation learning
our novel approach expands the capabilities of the robot s inverse kinematics solver empowering it to acquire a sequential repertoire of actions using tools of varying lengths
in this work we utilize proximal causal inference framework for learning optimal dynamic
treatment
dynamic treatment
in this work we utilize proximal causal inference framework for learning optimal dynamic treatment regimes when the unconfoundedness assumption fails
lastly we apply inputdsa to neural data recorded from rats performing a
cognitive
human cognition
lastly we apply inputdsa to neural data recorded from rats performing a cognitive task demonstrating that it identifies a transition from input-driven evidence accumulation to intrinsically-driven decision-making
these results confirm the effectiveness efficiency and robustness of our approach for low-resource
domain
models llms
these results confirm the effectiveness efficiency and robustness of our approach for low-resource domain adaptation of llms
to fully harness these electronic features the ability to tune the
fermi
fermi level
to fully harness these electronic features the ability to tune the fermi level relative to the band positions is needed
large language models llms commonly boost reasoning via sample-evaluate-ensemble decoders achieving
label
large language models llms
large language models llms commonly boost reasoning via sample-evaluate-ensemble decoders achieving label free gains without ground truth
we treat covid-19 and climate change as common pool resource
problems
climate change
we treat covid-19 and climate change as common pool resource problems that exemplify coupled human-environment systems
to evaluate our method we developed a task oriented
virtual
task performance
to evaluate our method we developed a task oriented virtual environment for a user study
however hr factors remain challenging to calculate from first principles complicated by convergence issues in excited-state relaxation and
time
first-principles calculations
however hr factors remain challenging to calculate from first principles complicated by convergence issues in excited-state relaxation and time consuming phonon calculations
in this work we advance this technique to generate
graphics-ready
video generation
in this work we advance this technique to generate graphics-ready 3d scenes suitable for physically based rendering pbr relighting and simulation
in this work we take a step toward building a truly accurate
world
world models
in this work we take a step toward building a truly accurate world model by addressing a fundamental yet open problem constructing a model that can fully clone and overfit to a deterministic 3d world
we then separately solve a dirichlet problem for laplace s equation to synthesize a safe textit guidance field that encodes variable levels of caution around
obstacles
collision avoidance
we then separately solve a dirichlet problem for laplace s equation to synthesize a safe textit guidance field that encodes variable levels of caution around obstacles -- by enforcing a tunable flux boundary condition
our solution jointly optimizes the transmission
power
power allocation
our solution jointly optimizes the transmission power and the neural network split point
we show that assignment rules with more than one variable allow the estimation of a more comprehensive
set
randomized experiments
we show that assignment rules with more than one variable allow the estimation of a more comprehensive set of treatment effects relaxing in a research-driven style the local and sometimes limiting nature of univariate rd designs
we propose a new approach that reformulates the maximum
likelihood
maximum likelihood
we propose a new approach that reformulates the maximum likelihood estimation problem as an optimization problem with equilibrium constraints where both the structural parameters and the value functions are treated as decision variables
the results confirm an average improvement and efficiency of the proposed method compared to the
state-of-the-art
achieves state-of-the-art
the results confirm an average improvement and efficiency of the proposed method compared to the state-of-the-art approaches
adaptive multilevel newton a quadratically
convergent
accelerated gradient
adaptive multilevel newton a quadratically convergent optimization method
if the researcher is willing to postulate a no residual autocorrelation assumption and some units can be thought of as controls pvar can identify
average
treatment effect
if the researcher is willing to postulate a no residual autocorrelation assumption and some units can be thought of as controls pvar can identify average treatment effects on the treated
the bregman divergence encompasses various loss functions as special cases where the squared
loss
loss function
the bregman divergence encompasses various loss functions as special cases where the squared loss yields riesz regression and the kullback-leibler divergence yields entropy balancing
saddle point approximation and central limit
theorem
central limit theorem
saddle point approximation and central limit theorem for densities in high dimensions
we compare the star formation histories sfhs of the mqgs with the high-redshift galaxy stellar mass function from observations and simulated
quiescent
host galaxy
we compare the star formation histories sfhs of the mqgs with the high-redshift galaxy stellar mass function from observations and simulated quiescent galaxies at z 5 finding that the masses from the inferred mqg sfhs regularly exceed either observed or simulated high-redshift galaxies which suggests indicates that mer...
this article investigates the convergence properties of a relative-type inexact proximal
augmented
augmented lagrangian
this article investigates the convergence properties of a relative-type inexact proximal augmented lagrangian method ripalm for convex nonlinear programming a fundamental class of optimization problems with broad applications in science and engineering
the correct classification of products is another essential element in a sustainable
supply
supply chain
the correct classification of products is another essential element in a sustainable supply chain
in this work we extend our previous work on the extrapolation of single-time observables to demonstrate an efficient scheme for
computing
quantum channels
in this work we extend our previous work on the extrapolation of single-time observables to demonstrate an efficient scheme for computing two-time impurity correlation functions by combining the non-markovian quantum mpemba effect nmqmpe with a dynamical map-based framework for open quantum systems
generating networks that more accurately reflect real-world patterns is a significant topic within
complex
complex systems
generating networks that more accurately reflect real-world patterns is a significant topic within complex network research
implicit bias of per-sample adam on separable data departure from the
full-batch
debiased machine learning
implicit bias of per-sample adam on separable data departure from the full-batch regime
dc transport number studies reveal that the total
conductivity
heat conduction
dc transport number studies reveal that the total conductivity is dominated by ionic conduction 95
cross-platform evaluation of reasoning capabilities in
foundation
reasoning curriculum
cross-platform evaluation of reasoning capabilities in foundation models